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6:30 PM Networking over light refreshments
8:00 PM Conclusion

To apply for a spot, please go here. Space is limited. Free and open to the public. This is a hybrid event. 

For any questions, please email burrowsb@stanford.edu

Join us for a Japan-U.S. Startup Ecosystem Roundup, exploring the latest policy and market-driven opportunities for cross-border startup growth.

Designed for investors and corporates engaging with startups, the event will feature key voices in Japan-U.S. innovation.

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Are Megafunds Warping the Venture Market?

Good day. Beezer Clarkson, a partner at VC-fund investor Sapphire Partners, this week posted a detailed analysis under the provocative headline “Is Venture Broken?” In it, she examined whether megafunds are stomping their way into the earliest rounds, bloating valuations and possibly undercutting returns for everyone. 

“The concern seems to be that if megafunds are dominating at early [-stage], using investments at seed as option value on later rounds, mega-fund participation could be ‘breaking’ venture through their overspending—shifting how value is accruing—or not—at different stages,” she wrote.

After reviewing deal data, she concluded that venture remains intact—albeit with wildly dialed-up competition.

What’s your take: Are megafunds distorting early-stage investing, or by their sheer heft spurring boutique firms to make smarter bets? Or will high valuations make venture an even riskier bet? Please email responses to vcnews@wsj.com.

Last week, we asked how much more you think the surging venture secondary market will grow. The topic generated considerable discussion. Here are some of the edited and condensed responses:

John Wuestling, partner at StepStone Group: “We calculate that the 500 largest private venture-backed companies have a total market capitalization of $3.7 trillion, with holders of 5% of this equity value considering secondary market sales at any given time, for a total addressable market of $185 billion. As companies continue to delay IPOs (average time from initial funding to public offering is now 13 years) and reach unprecedented values, we see a future where secondary volumes approach IPO proceeds as one of the top mechanisms for liquidity in the asset class.”
 

Ben Slome, co-founder, New Vintage Partners: “With companies staying private longer and valuations still high, secondaries have shifted from being a niche tool to the main lever for liquidity. Policy changes may give the market another boost, but the direction of travel is already clear. Secondaries have plenty of room to run, and they’re becoming central to how venture actually works.”
 

Ravi Viswanathan, founder and managing partner at NewView Capital: “Secondaries currently remain just a fraction of total venture AUM. If the market scales to private-equity norms, annual volume could exceed $70 billion. The real question isn’t if the secondary market will grow, but how quickly.”
 

Don Butler, managing director at Thomvest Ventures: “I believe the secondary market will continue to grow. Where the secondary market remains constrained, however, is by the asymmetry that exists between those interested in selling and those interested in buying private company shares today. So as long as this asymmetry exists, this is more likely to drive greater liquidity in the top names in the secondary market and a bubble in the secondary-market valuations for these same names, rather than a broader increase in the ‘market’ itself.”
 

Chris Lawrence, managing partner at Labyrinth Capital Partners: “It’s true that the lack of distributions across private markets has driven more liquidity-solution transactions, and this has contributed to the bump in secondary volume. But make no mistake, secondaries will remain an innovative part of the private-market landscape and are set to continue their upward trajectory given their correlation to overall private-market investment.”

Oak HC/FT seeks $2 billion for sixth fund. Oak HC/FT is back on the fundraising trail, about three years after wrapping up its last main fund dedicated to investing in healthcare and financial-technology companies. The investment firm, which has offices in Stamford, Conn., and San Francisco, is looking to raise at least $2 billion for Oak HC/FT Partners VI, according to documents prepared for the $28.5 billion Teachers’ Retirement System of Louisiana, a modest increase on $1.94 billion of commitments the firm collected the last time around. Oak HC/FT invests in healthcare and financial-technology companies, largely in the U.S., according to the documents, prepared for the Louisiana retirement fund by pension consultant Hamilton Lane.

That is how much the world’s businesses are expected to spend on enterprise software this year, according to projections from Gartner.

Stada Eyes IPO in Autumn if Conditions Are Right

Private equity-backed Stada aims to launch an initial public offering this fall following a postponement this past spring, joining the scattering of companies queuing up to list before year-end. The German pharmaceutical company delayed plans to go public in April, citing geopolitical uncertainty and market volatility. Other companies like StubHub and Klarna also delayed IPOs earlier this year due to market volatility stemming from U.S. President Trump’s tariff policies. In the coming months, a handful of companies are planning to list after the number of IPOs on European exchanges in the first half of 2025 fell to its lowest point since the start of 2020—with 46 listings, according to data from Dealogic.

Taco Bell Rethinks Future of Voice AI at the Drive-Through

The most transformative technology in over a century may have finally found its limit: ordering tacos. Since last year, Taco Bell has rolled out voice AI-powered ordering at more than 500 drive-through locations, and now the chain is realizing that not every customer is a fan of the new tech. It is the latest sign that nearly three years into the generative AI boom, companies are still simply figuring things out.

European investor Speedinvest said Will Wells joined the firm to lead its deep-tech team. He was previously a venture partner at both Lightspeed Venture Partners and Firstminute Capital.

Specialty care network provider Carrum Health appointed Andrew Steinberg as chief financial officer and Richard Eskew as chief legal officer. Steinberg most recently served as CFO at Honor. Eskew was previously at Accolade.

Cybersecurity company CrowdStrike plans to acquire data observability platform Onum for an undisclosed amount.

Framer, a website design platform based in Amsterdam and San Francisco, scored $100 million in Series D funding led by Meritech and Atomico, valuing the company at $2 billion.

Rain, a New York-based stablecoin infrastructure startup, grabbed $58 million in Series B funding. Sapphire Ventures led the round, which included participation from Dragonfly, Lightspeed Venture Partners and Norwest. Jai Das of Sapphire Ventures joined the company’s board.

InstaLILY AI, a New York-based platform that automates sales, service and operations across industries that rely on complex distribution, landed $25 million in Series A funding. Insight Partners led the round, which included participation from Perceptive Ventures and Marvin Ventures.

Aurelian, a Seattle-based AI startup that automates nonemergency calls for 911 centers, secured $14 million in Series A financing led by New Enterprise Associates.

Terraton, a San Francisco-based startup that is scaling biochar carbon removal in emerging markets, raised $11.5 million in seed funding co-led by Lowercarbon Capital and Gigascale Capital.

Central, an autonomous back-office platform built for startups, snagged $8.6 million in seed funding. First Round Capital led the round, which included participation from Y Combinator, Ritual Capital and Alumni Ventures.

Welcome Tech, a digital platform serving immigrant workforces, picked up a $7.5 million investment from TTV Capital, Westbound Equity Partners and others.

Heave, a St. Petersburg, Fla.-based startup connecting construction companies with on-demand heavy-equipment mechanics, fetched $7 million in Series A funding. Outsiders Fund led the investment, which included contributions from FJ Labs, Long Journey Ventures and Slow Ventures.

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Founders No Longer Need to Be In at the Founding

This newsletter was compiled by Matthew Strozier and Zachary Cole.

WSJ Pro Venture Capital is a premium service of The Wall Street Journal. We cover venture capital and the global startup ecosystem. Share your tips, comments and questions: vcnews@wsj.com

The Team: Matthew Strozier, Yuliya Chernova, Brian Gormley and Marc Vartabedian.

Megafunds aggressive early-stage participation is inflating competition and valuations, forcing smaller firms to adapt while raising concerns about returns.

Why some investors see a red flag if founders aren’t using AI

Where trust, tone and human judgment still matter most

On the pitch call, nobody knows it’s your AI doing the talking.

AI has become more than a tool for Silicon Valley. It’s now a gatekeeper shaping interactions between founders and VCs.

Marina Davidova, co-founder and managing partner at Davidovs Venture Collective (DVC), says her team has replaced much of the traditional analyst layer with AI agents. Instead of junior staff spending a day pulling data and drafting a memo, an agent can do it in minutes, and at a fraction of the cost.

The firm has backed more than 120 early-stage AI startups, and Davidova says those same systems parse founder updates across the portfolio and flag which investors or operators could help with hiring, sales or partnerships.

The approach even extends to Series A strategy: DVC’s algorithms monitor seed companies, predict when they’re about to raise and let the firm offer a cap table slot before the round becomes oversubscribed.

“AI isn’t just a tool for us, it’s the backbone of our operations,” Davidova told me.

Venture firms using AI like this is nothing new. AI-powered processes for sector analysis and conducting due diligence run throughout venture firms, and increasingly on the founder side, too.

It’s well documented that entrepreneurs are using AI to stay lean, keep their costs down and then communicate their updates to investors. Some task their agents to handle first-contact emails, portfolio updates or polish their pitch decks. Others rely on them to prepare data rooms and market comps that previously took weeks.

Are VCs okay with this shift? It depends on who you ask.

For Navin Chaddha at Mayfield, his answer is not just yes. He expects it. In his view, if a founder isn’t using AI, then that’s a warning sign.

“It’s a red flag if they’re not taking advantage of these tools,” he said.

Founders don’t get extra credit for using AI, but increasingly, not using these tools at all can raise questions.

What Chaddha is watching for is whether founders show judgment. He’s fine with AI-polished decks or agent-drafted updates, but the entrepreneur working with an investor still has to edit, contextualize and own the output. Sending untouched AI prose undermines confidence, Chaddha said.

Chaddha has also embraced AI as a workflow accelerant. His team runs AI comparisons of updated decks, uses agents to summarize key points, and surfaces signals about which founders are most active in open source or who’s vesting out of big tech.

But he draws a line. A board-level investor, in his words, still has to read the material. AI can speed the prep work, but it can’t substitute for conviction.

For him, the question isn’t whether AI belongs in founder–VC communications, it’s how skillfully founders use it as part of their process.

Don Butler at Thomvest has been on a similar path, but with a twist: he’s learning what AI means for the venture firm itself.

His team uses Gemini inside Google Sheets to condense notes from founder meetings into highlight reels. He called it useful, but said it required iteration.

“When we asked Gemini to summarize the way a reporter would, every company suddenly looked tremendous, even if they were behind plan,” he said.

Tone, it turns out, is tricky to nail down.

With more firms like DVC and Thomvest using AI tools to analyze company data, what happens to the role of the analyst?

Butler sees a parallel between analysts in venture today and coders a decade ago. Both roles, he suggests, are being augmented by AI at first, then potentially replaced.

“We could soon see vibe coding for spreadsheets,” he said.

It’s not just founders who are under pressure to use agents smartly. Firms are, too, a shift that may reshape who works in them and how they scale.

And if AI can generate polished decks with a click, does the pitch deck still matter? Patrick Mebus, co-founder of techtrust.ai, an investor platform that uses AI to streamline diligence and portfolio support, believes the pitch deck itself is on the way out.

“Once AI makes it trivial to generate 20 polished slides, the real interaction will happen elsewhere,” he told me.

Declaring the death of pitch decks is provocative, but it points to a deeper change. Format and medium are no longer fixed. Founders can send a memo, a deck, a Loom video or task an agent to create the first draft of all three. The information matters less than the process.

Where Chaddha sees AI as table stakes and Butler frames it as analyst augmentation, Mebus sees structures dissolving. To Mebus, AI’s rise may render the classic pitch deck as outdated as a faxed executive summary.

How Founders Use AI to Run Lean and Talk to VCs

For founders themselves, AI is less about revolution and more about survival.

Lucas Dickey, co-founder of Deepcast, a startup building a platform for podcast discoverability and engagement, told me that running lean isn’t optional at the early stage, it’s a must.

AI and automation are part of that reality. They’re tools to move faster and stretch scarce bandwidth.

But when it comes to working with VCs, the tools don’t change the fundamentals.

“What matters is clarity and alignment,” Dickey said. A polished deck is fine, but if the story doesn’t match the way the company is actually building, investors will pick up on it.

For Dickey, AI-aided communications don’t replace the hard work of building trust. No matter how polished the materials, misalignment between a company’s narrative and its substance is quickly exposed.

“Tech can help you ship faster or polish materials, but what matters is that investors know where you’re headed and why,” Dickey told me in a recent podcast conversation that will be published shortly.

His view sharpens the debate. Founders may lean on agents, but inauthentic updates backfire.

Some Investors Are Skeptical of AI-Written Updates

That sentiment resonates with Hunter Walk at Homebrew. He’s seeing more AI-polished updates, but too many seem generic.

“They’re easy to ignore,” he responded to me in an email.

That doesn’t mean he dismisses AI outright. He admits decks now come with MBA-grade industry charts, and investor updates are cleaner thanks to summarization tools. But he insists the “last mile” still belongs to the founder and without judgment polish won’t help.

He’s also recalibrating what he expects from technical founders. With AI accelerating product development, he assumes founders can ship a minimum viable product faster than ever.

“If you’re waiting for a fundraise to start vibe-coding your MVP, that’s a warning sign,” he said. The hard problems — of distribution and hiring — remain squarely in human hands.

Charles Hudson at Precursor Ventures has noticed the flood, too. The rise of AI outreach hasn’t necessarily improved quality.

“It’s more voluminous,” he said, even if it’s not much better than the cold emails that came before.

What worries him is sameness. There are 10 teams chasing the same problem with the same models and the same AI-generated pitch. “Sometimes the only difference is the names of the founders,” Hudson told me.

He also recognizes the pressure running top-down, as venture-backed CEOs are having to answer to their board demands to know “all the things that they’re doing with AI to save the company money.”

For Hudson, it isn’t whether founders use AI, but how much of their story is built on it, and whether any differentiation remains.

Taken together, these perspectives sketch the outlines of a new dynamic that is continuing to evolve.

Whereas some investors see the use of AI by founders as table stakes, Mebus believes it will ultimately dissolve the pitch deck. Meanwhile, more venture firms are incorporating AI inside their own operations, and as Butler said, that could reduce the role of analysts and associates, who are typically the first contact for startup founders.

I’ve heard from investors, similar to Walk and Hudson, who are receiving a lot of generic AI-generated spam in their inboxes.

And speaking on behalf of founders, Dickey reminds us that trust is still the coin of the realm.

As Davidova put it, AI isn’t just a thought experiment. She’s convinced founders will keep leaning on agents to cut costs and move faster. But she also knows that no matter how many memos an AI tool can draft, conviction and trust still come from people.

“AI isn’t a side tool anymore. It’s the operating system for how venture gets done,” she said.

In other words, founders can have their AI do the talking.

But what investors really want to hear is the founder’s own voice.

How founders use AI to pitch and update—and how investors are using the same tools to judge them

Given both historic growth in the venture industry and the number of venture-backed companies, it should come as no surprise that peer-to-peer mergers in the startup ecosystem have become increasingly common. With an 18% uptick in the number of VC-backed startup acquisitions by other VC-backed buyers in the first half of 2025 and likely more such deals to come, I wanted to share some of the lessons learned from being on both the buying and selling side of such transactions.

For brevity, I focus on lessons learned with regards to two particular topics for any startup team considering this exit path: the process of identifying the right partners and managing key constituencies.

Defining the ‘industrial logic’ of a merger

When evaluating potential companies to combine with, consider first and foremost the industrial logic behind doing so. Is your market growing fast enough that you feel the need to grab a larger share within your existing market?

If the answer is yes, then this would steer you toward looking more in the direction of potential erstwhile competitors. This can be a difficult choice for many founding teams.

But if your market is indeed a case of being at the right place and at the right time, then combining forces can create meaningful scale, particularly if your company is not the largest vendor in the space.

We’ve seen several instances in which two smaller participants in a market have used this approach in order to have enough scale to take on the market share leader or to go public. We can see this, for instance, in the merger between Forge Global and Sharepost to form Forge, which created enough scale to compete successfully against Nasdaq Private Market as well as to eventually go public.

Choosing between competitors and adjacent market players

On the other hand, if you think your company’s product should be part of a larger suite to serve your customers, it can be an easier path that potentially opens up far more options for partnering across adjacent markets.

One of the exercises that’s been found most interesting has been to meet with customers to review their day-to-day workflow, as this can help identify which products or services are used before or after yours and thus help identify ideal merger candidates.

Let customer workflows guide partner selection

Having been on the board of two companies that followed this approach to identify and ultimately acquire other startups, I found in both instances that customers were taking data from the SaaS offerings of the companies acquired and uploading it into the other offerings as part of their workflow.

In both cases, enterprise customers asked if they could integrate the two offerings to work together via API, and in one case, we had two different customers recommend that we merge, which we eventually did.

Having your customers ask you to merge is a powerful motivator. This also offers the opportunity for two companies to review their customer lists to understand not only how prevalent they are used together but also to identify opportunities for cross-selling in the future.

Additionally, the advent of AI agents is going to drive an emphasis on workflow automation. The customer relationships, data assets and workflow understanding of startups in adjacent areas are going to become prized assets and will drive a significant ramp in peer-to-peer M&A.

Managing stakeholder expectations beyond customers

Hand-in-hand with partner selection is managing the other constituencies beyond customers around the table. A successful merger requires buy-in from the boards, shareholders and key executives of both companies to typically come together.

Here, you have to manage not only the ongoing execution at the business, but also expectations. The obvious factors are expectations around leadership of the combined company going forward, valuation, ownership and governance.

One of the complexities of the exit process is that you are managing these in two different scenarios and comparing both: You are contrasting expectations around what happens in the event of a potential merger versus what happens if you remain on the current path of the business.

Balancing valuation, leadership and governance concerns

While peer M&A can be complicated to manage, the reality is that if the two teams see a better state together than independent, the executives and the shareholders can iterate to find a solution that works.

Where there’s a will, there’s a way, and that often draws on creativity or compromises that were not foreseen at the outset of a process. In particular, if the industrial logic is strong there are solutions that can be easily achieved if the parties are reasonable and there is mutual interest in making it happen.

Don Butler is a managing director at Thomvest Ventures, a $750 million evergreen VC fund founded by Peter Thomson (Thomson Reuters). His investments are focused on financial technology and marketing technology companies that leverage emerging and persistent data sources to better acquire and serve customers.

One of the biggest challenges for startup teams is the constant need to wear multiple hats. Startups with limited resources and a small team often must take on responsibilities beyond their initial skill sets. The best way to navigate this challenge is to implement structured professional development plans that help your team learn as they grow.

Merging To Create Scale: 5 Lessons Learned From Combining Private Companies  

Set in the heart of the city, the event was more than just a social gathering — it was a reflection of Thomvest’s long-standing commitment to people and ideas that drive progress. Attendees included early-stage founders, operators, and fellow investors, all aligned around the shared goal of building and scaling meaningful ventures.

From casual conversations to insightful discussions about market shifts, AI, fintech, and responsible capital, the energy in the room reminded us why we do what we do: we invest in people first.

For over 25 years, Thomvest has quietly partnered with exceptional teams to help them navigate risk, think long-term, and reach outsized outcomes. Events like Midtown Happy Hour give us the opportunity to celebrate that journey — not just with term sheets, but with real conversations and genuine collaboration

We’re grateful to everyone who joined us and look forward to continuing the dialogue in the months ahead.

On March 27th, 2024, Thomvest gathered founders, investors, and long-time collaborators for a special Midtown Happy Hour — an invitation-only evening dedicated to building stronger relationships in the innovation and investment community.

Midtown Happy Hour: An Evening of Connection & Opportunity

We’ve seen recently that a number of venture firms are looking to acquire mature businesses and apply AI to drive growth and efficiency. That speaks to the opportunity that we see in this latest revolution, and we expect to see more of this type of activity going forward. While much of the reporting has focused on this as a reason for VCs to enter private equity, I also see a structural aspect of venture that I believe will compel firms to move into private equity; namely, the structural imbalance between the number of startups that venture firms have invested in relative to the rate at which these are being acquired.

To set the stage, recall that the best companies in venture drive the majority of returns in the industry. The attempt to invest in and build those companies - which typically scale past $100mm in ARR and keep growing with increasingly efficient unit economics - has led VCs to fund a significant number of companies. 

A query of PitchBook’s data shows over 54k VC-backed companies in existence in the US, with 28k seed companies, 14k series A companies, 6k series B companies, 2.8k series C companies, and 1.2k series D companies as of May 2025. Contrast the sizable inventory of startups with the more tempered pace at which exits are happening as seen in the graph above, showing the number of exits by stage for VC-backed companies over the last decade.

How Long Could it Take to See VC-Backed Companies Exit?

If we contrast the inventory of companies with the number of exits at their respective stages, this has averaged over the last decade around 200 Series A company exits per year, 130 Series B company exits per year, 80 Series C company exits per year, and 90 Series D (or later) company exits per year. At that rate, considering just the most mature companies at the Series D stage, we would need about 1.2k / 90 = 13 years for these companies to exit. If we look at the inventory of current Series C stage companies, the historic exit rate would imply roughly 35 years to remove the backlog of VC-backed companies.

Exits for startups typically come from getting acquired by a strategic or a private equity fund or going public. When looking at the distribution of exit types, we find that the average exit path over the last 10 years has been 73% acquisition, 19% buyout by a private equity firm, and 8% IPO. In past analyses, we’ve also seen that a meaningful percentage of startups at each stage either go out of business or continue on as private companies without raising subsequent rounds of financing.

If the volume of exits is not there, could the values associated with exits tell us something different? What we look at exits by dollar value, we find that the source of the best returns - the IPO market - has been effectively closed the last few years. IPOs generate the best outcomes in terms of total market capitalization, but the window at this point has closed for all but the largest startups.

Given the longer hold time for companies, we’ve already seen venture firms exercising fund extension rights with limited partners as well as establishing continuation funds to keep investing in portfolio companies. We’ve also seen venture firms increasingly look to sell stakes in their portfolio companies to secondary buyers as a way to generate distributions to limited partners.

The problem with these solutions is that they don’t match the scale of the inventory of good companies that exist. I believe that the natural evolution of venture will be to build out private-equity-like capabilities, whether through the addition of teams with PE experience or by raising funds specifically focused on rollup strategies. In effect, venture funds will move to a model where they can sponsor their existing companies to grow through acquisitions and drive scale and efficiency.

For entrepreneurs, this means that the exit strategy could increasingly be a focus on identifying complementary startups that they can merge with as part of this evolution. This trend has already begun over the last several years, and may become a meaningful exit path as venture funds increasingly look to drive scale and ultimately exits for their portfolio companies.

This is by no means an easy path, however. Venture companies tend to be concentrated in waves. At one point in the past we had identified at least 29 venture-funded antivirus software companies competing for that market. Today we see similar volumes of new companies being funded in similar markets in the current wave of AI companies. Building and scaling defensible data or distribution strategies and meaningful market shares will be required for this type of transition into more of a private equity-type model to work. We expect to see operators from private equity firms be brought onboard by the larger venture funds given the scale of the capital tied up in their portfolios over time. We’ve already seen investment bankers hired into capital markets or advisory roles at the larger funds, and I believe this type of rollup persona will become increasingly common in the years ahead. While there are plenty of opportunities to buy mature companies and drive efficiencies via AI, I believe the imbalance between the supply of good companies versus the volume of exits will by itself drive the transformation of our industry.

Will VCs develop their own private equity capabilities as a means of driving more exits int their portfolios?  As published originally on Forbes, the numbers present a compelling case for why this might happen.

Don Butler speaks to why AI may be a bigger shift than the internet for venture capital.

Why Professional Development is a Startup Superpower — A former boss of mine always said, "More sweat on the training field, less blood on the battlefield." This long-term mindset is essential for startups. As your company grows, so must the skills of your team. The time to build those skills isn't when a crisis hits — it's now. By planning ahead, you can identify what skills your company will need in six months or a year and start preparing your team accordingly. This proactive approach gives your startup a competitive edge while boosting employee satisfaction and retention.


Create A Professional Development Plan For Each of Your Employees — To make it easy for you to get started, I've attached a pro forma version of a professional development plan I've used for myself and numerous people I've managed. Click on the template. I'll walk you through the various elements you and your employee should first discuss and then fill in:

Training Process — This confirms the time period the employee will work with their manager and how often they will review progress made against this plan (as well as where additional effort is needed). Most professional development plans are on a year-long basis but can be for shorter periods if accelerated training is required.

Overall Training Objective — The employee and their manager must be thoughtful about identifying the "big idea" regarding where they want to focus the employee's training efforts. Realistically, the employee will only be able to tackle one or two of these overall training objectives in a year. Some examples of these include:

Develop Executive Presence — Enhance communication, persuasion, and influence skills.

Improve Strategic Decision-Making — Apply structured decision-making frameworks in key business decisions.

Strengthen Team Leadership — Implement leadership coaching and improve team engagement.

Master AI-Powered Marketing Analytics — Leverage AI concepts and tools to improve campaign effectiveness.

Since I'm familiar with marketing, I will use the last example of an overall training objective ("Master AI-Powered Marketing Analytics") for this article. I could have used any of the other examples (and many others) as a starting point, depending on what the employee and their manager want to focus on.

Performance Expectations— This takes the employee's overall training objective and breaks it into more manageable areas to focus on. For example, if the overall training objective is to master AI-powered marketing analytics, your performance objectives could include the following:

Learn statistical and machine learning concepts relevant to marketing analytics (e.g., predictive modeling and customer segmentation).

Conduct a pilot project using AI analytics to optimize audience targeting and content personalization.

Develop a reporting framework to measure AI-driven campaign performance and make iterative improvements.

Training Steps — This is where the development plan gets even more granular in terms of the specific training steps and actions the employee will take (with the help of their manager) to master the overall training objective and performance expectations. Continuing with the example from above, this might include the following details:

Enroll in a course or workshop on AI marketing platforms (e.g., Google Analytics 4, HubSpot AI, ChatGPT for marketing, Adobe Sensei, etc.).

Complete practical exercises using AI-driven insights to optimize real-time marketing campaigns.

Obtain certification in at least one AI marketing tool to validate proficiency.

There has never been a better time to access different ways to complete training on various skills and topics. Affordable​​ e-learning, virtual training, and AI-driven platforms have surged, reducing dependency on in-person workshops.

Mentors in your company and the industry are another valuable resource. Hundreds of online courses are available — one of my favorites is www.sectionschool.com. Your employee can also join professional networks, and assuming the company is willing to invest in this as a resource for the employee, there are individual coaching and team coaching opportunities.

What The Manager Will Do—The company must prioritize employee training, and managers must commit in writing to working closely with their employees on their development plans. Having worked with many outstanding employees over the years, I have witnessed employees often master new skills and take on new responsibilities based on their professional development plans. However, the employees' progress and development will suffer unless their manager is willing to take the time and effort to support them.

Projects and Initiatives Offering Training Opportunities — Learning a new skill is not enough — the employee needs to implement it in the business to master it. Once the employee and manager have agreed on their overall training objective, performance expectations, training steps, and what the manager will do to support them, they should spend time identifying ways the employee could apply these skills to grow the business.

For example, continuing with the example from above, the employee could develop a plan to analyze which aspects of the company's marketing programs could be improved via AI and start a test to prove the value of this before full implementation.

Plan the Work, Work the Plan — In the rush to do everything a startup needs to do, it takes a lot of discipline and focus to create a professional development plan for employees and their managers and to implement it closely with them.

Investing in employee growth doesn't require significant capital—just time, effort, and commitment. Developing professional development plans for your employees will require considerable work from your team. I suggest initially having several employees utilize a professional development plan with their managers. After a few months, get their feedback, and then, based on their results, consider leveraging it for the rest of your company.

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