SUCCESS

Presented by SalesforceInterested buyers don’t generate revenue. Live customers do. That’s the lesson I keep drawing from watching hundreds of ISV partnerships navigate the agent economy over the last 18 months.The companies pulling ahead aren’t winning on features. They’re winning because customers can move from discovery to live deployment in hours, while competitors are still negotiating contracts, clearing tax reviews, and waiting on provisioning.That gap between a buyer who says “yes” and a customer who is actually using the product is where too many deals lose momentum. Urgency fades. Champions move on. Competitors get another opening.Gutenburg saw that gap firsthand. Healthcare organizations valued its product, but sales cycles stretched 30 to 45 days. With custom pricing via AgentExchange, the company closed an urgent healthcare deal in just 48 hours.Not 48 days. 48 hours.The final contract phase alone dropped from 4 hours to 4 minutes. A 60x improvement.I see this pattern across the ISV ecosystem. Building agents is getting faster. Getting buyers live before urgency fades is becoming the constraint. In a market moving this quickly, that can matter as much as the agent itself.It’s like building a bullet train and selling tickets by fax. The product is built for speed. The transaction is not.Distribution beats product in crowded marketsNearly every software company is pouring resources into agent development. Far fewer are rethinking the path from discovery to deployment. Manual contracts, custom invoicing, tax reviews, provisioning delays, these are the handoffs that turn a 48-hour deal into a 45-day cycle.That friction is now a competitive disadvantage, because the buying process is changing faster than most back offices are. Gartner predicts that by 2028, 90% of B2B purchases will be guided by AI agents.That does not mean humans disappear from enterprise buying. It means the discovery and evaluation process changes. Buyers will increasingly use AI to identify, compare, and narrow solutions.If your agent is not discoverable where that evaluation is happening, you may never make the shortlist.A better agent can still lose to one that’s easier to buy.Domain expertise matters. Workflow depth matters. Proprietary data matters. Customer context matters.But enterprise categories are getting crowded fast. In crowded markets, the best product does not always win. The product that is easiest to discover, buy, deploy, and scale often has the advantage.As agent-guided buying takes hold, the first evaluation may happen before a demo is scheduled or a sales rep is in the room.AI agents will increasingly scan marketplaces, compare solutions, and help narrow purchase decisions in the time it used to take to schedule a discovery meeting.Companies that figure out marketplace distribution now will own their categories.That is the problem AgentExchange was built to address. It’s a single destination for apps, agents, and integrations that extend and connect to Salesforce and Slack, helping customers get more from their platform investments.But discovery is only the first step. The bigger question is what happens after the buyer says “yes”.“Yes” doesn’t mean liveEnterprise software teams spend enormous energy getting to “yes.” But in many deals, that is where the operational work begins.Between “yes” and “live,” the back office can generate a chain of handoffs: contracting, invoicing, tax calculation, licensing, provisioning, fulfillment, payment, and finance reconciliation. Every handoff delays activation for the customer and delays recognized revenue for you.For AI agents, that back-office drag is becoming a front-office problem.AgentExchange brings discovery, commerce, and activation together, helping partners manage custom pricing, billing, licensing, provisioning, and fulfillment through one connected experience.”AgentExchange removes the traditional procurement friction that slows deals. Customers can now discover, purchase, and deploy PandaDoc directly through their existing Salesforce contract, turning what used to be a multi-week process into a same-day activation.” Keith Rabkin, CEO at PandaDocWhat closing in 48 hours actually looks likeGutenburg’s 30-45 day cycles were eaten up by contract logistics. Sales moved faster than their back office.Using custom pricing and automated transaction capabilities through AgentExchange, they streamlined contracting, tax calculation, provisioning, and other steps between buyer interest and activation.When a healthcare organization needed a tool to help them create documents aligned to the Americans with Disabilities Act and accessibility requirements, Gutenburg closed in 48 hours from first contact.The 48-hour close is the differentiator. It is what efficient growth actually looks like in practice. Revenue scales without scaling headcount. Pipeline coverage improves because you are discoverable everywhere. Net recurring revenue increases because customers expand through the same frictionless channel.”AgentExchange condenses contracting and tax calculations into a 10-minute process with improved accuracy,” said Zamial Jones, VP of Customer Success at Gutenburg. “For partners spending hours on these tasks for every deal, that’s transformational.”The window is closing faster than you thinkThe app economy took a decade to mature.The agent economy won’t.The ISV partners I’ve watched pull ahead aren’t the ones with the most sophisticated agents. They’re the ones who treated distribution as a product problem — resourced, measured, and iterated — before the category consolidated around them. The ones still treating go-to-market as a post-launch consideration are consistently 6 to 12 months behind.You can spend the next two quarters perfecting your agent’s reasoning capabilities. Or you can spend them making sure customers can actually buy it.Salesforce is investing in the next generation of companies creating agents with $50 million through the AgentExchange Builders Initiative—capital, engineering support, co-marketing, and co-sell programs. Companies that move now will define what enterprise AI distribution looks like for the next decade. Learn more here.Lisa Eisenberg is SVP of ISV Partnerships at Salesforce.Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.

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Onsemi has spent several years working through weakness in its core automotive and industrial markets, and its latest quarter gave Wall Street a clearer look at where the next leg of growth could come from.The chipmaker reported second-quarter results on Aug. 3 that showed improving revenue, profitability and free cash flow. Onsemi (ON) also said its AI data-center business remains its fastest-growing operation, broadening a growth story long centered on autos and industrial chips.In a note given to TheStreet, Bank of America analyst Vivek Arya reiterated a Buy rating on Onsemi while lowering the firm’s price objective to $120 from $138. Based on the $80.40 share price listed in the note, the new target still implied roughly 49% upside.The target cut came alongside higher earnings estimates, creating an unusual setup: BofA is using a lower valuation multiple while arguing that Onsemi’s long-term earnings power could become substantially larger.Onsemi earnings strengthen the AI growth caseOnsemi reported second-quarter revenue of $1.604 billion, up 9% from a year earlier. Non-GAAP diluted earnings rose to $0.74 per share from $0.53 a year ago, while GAAP diluted EPS came in at $0.56.Free cash flow reached $425.4 million, roughly quadrupling from the prior-year period, while cash from operations increased 150%. CEO Hassane El-Khoury said revenue, gross margin and EPS finished above the midpoint of guidance, with strengthening demand particularly visible in AI-driven applications.Related: Duolingo earnings put a Wall Street warning to the testManagement now expects AI data-center revenue to more than double in 2026, while highlighting expanded participation in Nvidia’s MGX ecosystem and additional AI data-center platform wins.Onsemi guided third-quarter revenue to between $1.65 billion and $1.75 billion, with non-GAAP EPS between $0.81 and $0.93. The $1.70 billion revenue midpoint and $0.87 EPS midpoint both sit above the consensus figures cited in BofA’s note.

Onsemi reported second-quarter revenue of $1.604 billion, up 9% from a year earlier.Cheng Xin via Getty Images

Bank of America sees much bigger earnings power aheadBofA’s longer-term model goes well beyond the latest earnings beat. Arya raised his 2026 EPS estimate to $3.20 from $3.12 and his 2027 estimate to $4.57 from $4.26. The analyst forecasts EPS reaching $6.15 in 2028 and roughly $12 by 2030.BofA estimates revenue can rise from about $6.54 billion in 2026 to roughly $12.67 billion in 2030, an 18% compound annual growth rate.AI is the most aggressive piece of the forecast. Arya models AI and data-center sales climbing from roughly $250 million in 2025 to about $4.68 billion in 2030, representing a 67% CAGR. Automotive and industrial revenue are also expected to return to sustained growth.More SemiconductorsBank of America sets aggressive Tower Semiconductor targetCathie Wood buys $14.3 million of tumbling semiconductor stockVeteran strategist sends strong warning on semiconductor stocksMargins provide another lever. BofA believes gross margin can eventually reach 53%, helped by higher factory utilization, product mix, restructuring, and divestitures. Operating margin could approach 40% by 2030 in the firm’s model.Despite those higher estimates, BofA lowered the price target because it now applies a 20-times multiple to estimated 2028 earnings, down from the prior methodology of 32 times estimated 2027 earnings. Arya pointed to recent semiconductor-sector multiple contraction while arguing Onsemi still trades below its historical mid-teens range on 2028 estimates.Onsemi still has risks to work throughBofA sees rising input costs, including substrates and gold, as one potential pressure on gross margin. The analyst also pointed to legacy consumer and mobile exposure and execution risk tied to Onsemi’s planned Synaptics acquisition.Onsemi agreed in June to acquire Synaptics in an all-stock deal valued at roughly $7 billion. The company expects the transaction to close in mid-2027, subject to shareholder and regulatory approvals, and said the deal would expand its capabilities in connected compute and edge AI.For BofA, the latest quarter provides evidence that the earnings recovery has started, but the larger call stretches several years beyond one earnings report. The $120 target is still bullish, while the more consequential forecast is the possibility that AI growth and margin expansion could push Onsemi toward roughly $12 in annual earnings per share by 2030.Related: Biggest AI risk for investors emerges in cybersecurity

When a startup employee sits across from a recruiter and receives an offer, one part of the package has always been almost impossible to evaluate on the spot. The salary is straightforward. The benefits are standard. The equity grant is something else entirely. Twenty thousand options. Is that competitive? Compared to what?Companies have always been able to answer that question. They buy benchmarking data. But the person on the other side of the table, the one deciding whether to sign, has generally had very little to go on.The equity information gap startup employees have negotiated aroundSalary transparency has improved dramatically over the past decade. Levels.fyi,Glassdoor and LinkedIn have made it possible for most workers to check a salary offer against real market data before accepting. Several states now require employers to post pay ranges on job listings. The information asymmetry that once defined salary negotiations has narrowed considerably.More Tech:ServiceNow’s quiet $1B cybersecurity boomA European rival to SpaceX is chasing a $2B valuationSK Hynix denies Intel Ohio fab deal, but the market didn’t careEquity has not followed the same path. Unlike salary, equity data has never been subject to transparency laws. And unlike stock compensation at public companies, startup option grants don’t appear in any filing. The result is that employees at private startups have been negotiating one of the most consequential parts of their compensation package largely blind, while the companies they’re negotiating with have access to detailed benchmarking data through paid services.This is the gap that a growing number of tools are trying to close. One of the more notable recent attempts is Equitybee Benchmark, a free tool that lets U.S. startup employees compare equity grants across roles, seniority levels, departments, and company stages. The data behind it come from more than 9,000 verified option grants across over 2,500 U.S. startups, from Seed through Pre-IPO. Unlike salary surveys, these are not self-reported estimates. They are verified grants, addressing what a blog post from Aption described as the core problem for early employees: They “rarely see the full capitalization table, the liquidation preferences sitting ahead of them, or the precise terms of the last priced round.”What the data behind Equitybee Benchmark actually measureOption count alone tells you almost nothing useful. The same 20,000 options can be worth wildly different amounts, depending on the company’s valuation at the time they were granted. Equitybee Benchmark addresses this by comparing grants using Fair Market Value at the time the grant was issued. Options multiplied by FMV per share gives a grant value. Ten thousand options at a $10 FMV equals a $100,000 grant. That is the number you can actually compare across companies and roles.From there, the data can show how grants differ by department, seniority, and company stage. Do engineers consistently receive larger grants than marketers? How much equity typically increases with seniority? Do later-stage companies grant differently from early-stage ones? These are questions that HR teams have always been able to answer internally. Employees have had to guess.The tool is deliberate about what it does not claim to do. It doesn’t predict whether a company will exit. It doesn’t tell you what your options will be worth. It can’t, because nobody can. What it does provide is the same market context that companies have always accessed, applied to the employee side of the negotiation for once.

For decades the information asymmetry in startup comp ran one direction.Getty Images

Four moments when equity data changes a decisionKnowing where an equity grant stands relative to the market matters most in a handful of specific situations. Evaluating a new job offer is the obvious one. But it also applies when preparing for a promotion conversation where equity is part of the ask, when weighing whether to leave one company for another, or when trying to make sense of grants already held without any external reference point.The timing of tools like this is not incidental. IPO activity has been picking up after a quiet stretch, and the AI hiring wave has pushed startup compensation to levels not seen in years. Equity is accounting for a larger share of total startup pay than it has been in some time. The pressure on employees to evaluate grants accurately has increased at exactly the moment when doing so has become slightly more possible.For decades, the information asymmetry in startup comp ran in one direction. Companies had the data. Employees had a hunch. Salary transparency laws and crowdsourced salary tools have started closing that gap on the cash side of the equation. Equity is the last major piece that hasn’t had a public market for its information. That is slowly starting to change, and for startup employees negotiating one of the most valuable and least understood parts of their compensation, the direction of that change matters.Related: Microsoft offers laid-off employees generous package

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Wallets and apps on Solana can now tap MoneyGram’s global network to move between digital assets and local currencies.