Block
About two and a half years ago, CEO Jack Dorsey sensed the industry was shifting and created a weekly executive meeting with 40 of the company's top leaders to discuss emerging trends. Donjie Prasanna, then a part-time senior engineer helping one of the engineering teams while raising a young child, observed that despite discussing many important topics, no one was paying serious attention to AI. He wrote a letter to Dorsey arguing that Block needed to become an AI-native company, not just adopt AI tools. After Dorsey visited Sydney and spent two days walking and talking with Donjie, he offered him the CTO role. "It's like, be careful what you're good at," Donjie recalled.
Goose started as an internal desktop tool and AI agent built on top of large language models like Claude and OpenAI's GPT. What made it different from existing AI chatbots was the Model Context Protocol (MCP)—formalized wrappers that exposed enterprise tools like Salesforce, Snowflake, and SQL databases to the LLM. "Until that point, the LLMs were not really able to do much other than chat. But goose gives these brains, arms and legs to go out and act in our digital world," Donjie explained. The tool could orchestrate complex workflows: a user could ask it to build a marketing report, and Goose would write SQL queries, analyze data in Python, generate JavaScript charts, and email the final PDF—all without human intervention. One engineer even had Goose watch his screen 24/7, anticipate his needs from Slack conversations, and open pull requests for features before he'd finished discussing them.
Block didn't need to find external customers—they had thousands within their own organization. But adoption required cultural change. Donjie's first move was reorganizing Block from a GM (general manager) structure, where each business unit (Square, Cash App, Afterpay) operated independently with separate engineering teams, to a functional structure where all engineers reported to a single head of engineering. This was painful but essential: "Conway's law can be really, really powerful... you ship your org structure." With functional teams aligned around shared tools and language, Goose became the natural hub for AI automation. Engineers, support teams, legal teams, and risk management teams all began using it. Non-technical people building internal software tools saw the most dramatic gains—weeks of work compressed into hours.
Block measured success through multiple lenses. Engineering teams using Goose daily reported saving 8-10 hours per week. Across the company, data scientists calculated that AI tools were saving roughly 25% of manual hours. But Donjie was candid about limitations: AI excelled at routine tasks, automating UI tests, and helping non-technical teams build tools, but still underperformed humans on deep architectural decisions, race conditions, and design judgment. The biggest productivity win wasn't AI at all—it was the organizational restructuring that reduced silos and aligned technical strategy across the company.
Goose also showed unexpected use cases. Gosling, a mobile version for Android automation, transformed QA by replacing armies of contractors clicking through screens. One risk management team built an entire self-service system for enterprise risk—work that would have been queued for months on a product roadmap.
Instead of holding Goose as proprietary technology, Block open-sourced it completely. "We believe in the power of open source," Donjie said. The decision paid off: Databricks, mid-tier tech companies, and even competitors began adopting Goose. Donjie was pushing the boundaries further, experimenting with agents that work for hours autonomously overnight, anticipating what engineers want to build before they articulate it. He was rewriting features from scratch daily, embracing a world where AI makes continuous delivery and zero-based design possible. For hiring, Block shifted from viewing engineers as commodities to seeking people with a learning mindset—not necessarily AI experts, but those eager to master these tools and rethink how software gets built. The future Donjie envisioned wasn't one engineer with four jobs, but teams where humans set the goals and guard the taste while AI handles the execution.
- •By solving an acute internal pain point (lack of AI integration) that the CEO personally validated through direct conversation, Block created a tool with built-in product-market fit before seeking external customers.
- •Reorganizing from siloed business units to functional engineering teams aligned the entire organization around a single platform, making Goose the natural hub for workflow automation and dramatically increasing adoption velocity.
- •Giving the AI agent concrete capabilities through the Model Context Protocol—exposing real enterprise tools rather than limiting it to chat—transformed it from a novelty into a force multiplier that could orchestrate end-to-end workflows autonomously.
- •Measuring impact quantitatively (8-10 hours/week per team, 25% manual hour reduction company-wide) and being transparent about limitations built credibility and enabled teams to deploy Goose only where it genuinely outperformed humans.
- 1.Identify a strategic gap your leadership is discussing but not acting on, then write a clear, evidence-based case to a decision-maker and request a direct conversation to explore the opportunity together.
- 2.Build your MVP as an internal tool solving a real workflow bottleneck for your own team, using APIs and protocol wrappers to connect it to the actual systems your users work with daily.
- 3.Restructure your organization so that the teams, tools, and incentives are aligned around the new solution—eliminate silos that would compete with or fragment adoption of the platform.
- 4.Track and publicly share concrete metrics (hours saved, volume of tasks automated, failure modes) to establish credibility and help teams understand where the tool adds genuine value versus where human judgment remains essential.
Similar Companies
247.ai
$25.0M/mo247.ai, founded by PV Cannon in 2000, is an AI-powered customer service automation platform serving over 150 enterprise customers with $300M+ in ARR. The company raised only $20M from Sequoia (2003) and bootstrap, achieving 10% net profit margins while maintaining a 12-month CAC payback period and 100% net revenue retention. Despite a security breach setback around 2018, 247.ai has recovered and recently achieved 20% new revenue booking growth in their best quarter.
iCIMS
$13.3M/moiCIMS is a bootstrapped SaaS provider founded in 1999 that dominates the talent acquisition software market as the #2 player, serving 3,500 enterprise customers with an average monthly spend of $4,000. The company exited 2017 with $160M ARR and is targeting 25%+ annual growth while maintaining profitability, recently acquiring Text Recruit to expand into candidate messaging and recruitment advertising.
Zoom
$12.0M/moZoom is a freemium SaaS video conferencing platform founded by Eric Yuan in July 2011 after he left Cisco to build a next-generation collaboration solution. The company has grown to 850,000+ paying customers across individual, SMB, and enterprise segments, generating over $12M in monthly recurring revenue with approximately 100% year-over-year growth. Rather than focusing on customer stickiness or aggressive growth targets, Zoom emphasizes customer happiness and organic word-of-mouth acquisition, which has proven highly effective in driving viral adoption.
Madwire
$10.0M/moMadwire is a comprehensive SaaS platform for small businesses (1-100 employees) that combines CRM, payments, invoicing, billing, e-commerce, and multi-channel marketing tools in a single platform. Founded in 2009, the company has grown to $120M ARR serving 20,000 customers with an average revenue per user of $500/month, while maintaining strong unit economics ($3,000-$4,000 CAC with 3-month payback) and recently turning profitable with a focus on reaching 15-20% EBITDA margins. The company is exploring an IPO within 12-18 months without having raised substantial capital beyond an initial $7.5M.
Plunge
$10.0M/moPlunge is a hardware company that manufactures and sells at-home cold plunge devices. Founded in 2020 by Ryan Duey and Michael after their brick-and-mortar float therapy and sauna businesses were impacted by COVID, the company grew from $270k in first-year revenue to $120M+ ARR in four years. Their success is driven by influencer gifting, organic word-of-mouth, and highly efficient paid advertising (7-10x ROAS on Facebook and Google).