Founder, CEO & Product Executive
AI-Native B2B SaaS · 0 to 1 & Enterprise Scale
Two-time founder & product leader. Product doesn't ship from a corner office, so the work I care about is building the teams that ship it. At Waypoint AI that's a distributed product, engineering & go-to-market team across Europe & the US, serving customers including Volvo Cars, ClickHouse, Agiloft & Waldner AG. Earlier I led product & channel teams at WorkBoard & Proofpoint.
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I build products, teams & companies in enterprise software & AI. Taking a B2B platform from early stage to enterprise adoption is a team sport: hire people with judgment, hand them the real problem & the context to solve it, then turn complex technical capability into something customers actually want to use.
About Steve Boogar
Steve Boogar is a product & operating executive and two-time founder. He is cofounder & CEO of Waypoint AI, an enterprise AI agent orchestration platform backed by a $3.1M pre-seed led by 42CAP & Dreamcraft Ventures, with Berkeley SkyDeck Fund & Lumière AI Ventures. He was previously Director of Product Management at WorkBoard and product owner for the small & medium business segment at Proofpoint, where he scaled Proofpoint Essentials from $12M to $50M ARR. Earlier he was cofounder & COO of FarmX and a U.S. Air Force officer on the GPS Block III satellite program.
He holds an MBA from the University of California, Berkeley, Haas School of Business, a master's degree from the Naval Postgraduate School & a BS from the United States Air Force Academy. He is a two-time Berkeley SkyDeck alum, with FarmX in 2015 & Waypoint AI in 2024.
Profiles & citations
- LinkedIn — linkedin.com/in/stephenboogar
- Waypoint AI — mywaypoint.ai
- Waypoint AI raises $3.1M pre-seed — Yahoo Finance
Not affiliated with BoogarLists, Boogar Associates or any venture-directory publisher, which are a different person. The correct LinkedIn profile is /in/stephenboogar.
Experience
Cofounder & CEO
Waypoint AI
Building an enterprise AI agent orchestration platform for B2B software companies. It automates knowledge work across support operations, engineering analysis, quality & compliance and legal, working inside the Jira, Salesforce & ServiceNow systems customers already run.
- Raised $3.1M pre-seed from 42CAP, Dreamcraft Ventures, Berkeley SkyDeck Fund & Lumière AI Ventures
- Working with enterprise clients including Volvo Cars, ClickHouse, Agiloft & Waldner AG
- Built & lead a distributed cross-functional team across Europe & the US, hiring across product, engineering & go-to-market
- Berkeley SkyDeck 2024 cohort
Director of Product Management
WorkBoard
Senior Product Manager 2021 · Group Product Manager 2021 - 2023 · Director 2023 - 2024
Led product strategy for operating rhythm products at a leading OKR and business execution platform. Shipped features used by enterprise customers to run more efficient business reviews and optimize operational cadence.
- Launched WorkBoard Scorecards, enabling teams to replace 30-hour manual deck creation with automated, data-driven dashboards
- Owned product roadmap for operating rhythm products including MBRs and QBRs
- 75.8% of surveyed users reported Scorecards helped them run smarter, more efficient reviews
Manager, Product Management
Proofpoint
Product Manager 2017 - 2019 · Manager, Product Management 2019 - 2021
Enterprise cybersecurity & email security.
- Scaled Proofpoint Essentials from $12M to $50M ARR, owning product & go-to-market for the SMB segment across roadmap, packaging & commercial motion
- Led a global channel sales team of 8 across the US, UK & Australia, presenting annually at executive QBRs & Proofpoint SKO
- Developed strategy, planning & keynote content for the EVP/GM of Proofpoint's core email security business
Cofounder & COO
FarmX
Precision agriculture & IoT startup. UC Berkeley SkyDeck 2015.
- Cofounded the company & raised a $2.5M seed
- Shipped solar-powered IoT hardware & cloud-based field management software for farm automation, multi-network & IP68-rated for permanent outdoor installation
- Ran operations from zero across sales & supply chain
Officer, Captain
United States Air Force
Served as an officer in finance and acquisitions roles, managing budgets and procurement processes for major defense programs.
- Supported acquisition and financial management for GPS Block III satellite program, the next-generation GPS modernization effort
- Managed budgets and procurement processes for critical defense operations
Earlier: Corporate Strategy & Business Development
Harris Corporation · HPE · GE Oil & Gas · Cisco
Strategy, commercial & business development roles across aerospace, enterprise software & industrial equipment, between the Air Force and product leadership.
- Harris Corporation - Strategy & Business Development Manager, Commercial Small Satellites: led go-to-market & business development for commercial small satellite products, hitting 100% of the FY16 plan & signing partnership MOUs with Loft Orbital & ConocoPhillips
- Hewlett Packard Enterprise - Corporate Strategy, Enterprise Software: global sales-operations performance analysis & a vendor-selection analysis that informed a CEO-level decision. Named Corporate Strategist of the Semester
- GE Oil & Gas - Commercial Manager, Subsea Drilling Systems: led cross-functional teams bidding technical proposals to clients across five continents
- Cisco - Strategy, Internet of Everything: authored an IoT thought-leadership whitepaper
What I'm Building
Side projects, built nights & weekends. Each one started as a question I wanted a real answer to.
A second brain that rewrites itself
40+ Claude Code routines maintain my working notes on a schedule & rewrite their own prompts from their own scores.
What it does & what it is built on
My working notes live in an Obsidian vault that 40+ Claude Code routines read from & write to on a schedule.
- Routines cover product intelligence, competitive scanning, meeting prep, content drafting & a nightly journal that aggregates every other routine's output into one entry.
- Every routine grades its own output against a rubric & rewrites its own prompt from the score. What runs today is not what I originally wrote. I did not hand-edit most of the difference.
- One routine exercises a codebase against a library of use cases & an open-gap backlog every day, so drift shows up as a diff instead of a surprise.
- Meetings are captured by webhook, transcribed & then read back against what the vault already knows, so a decision made out loud lands next to the document it contradicts.
- A tracker watches chat channels, merge requests & standup notes to compare the plan against what actually shipped.
- The vault argues with itself. A contradiction pass looks for claims that no longer agree across documents & surfaces them rather than letting the newest file quietly win.
- One routine audits all the others against canonical patterns. It is the only reason 40+ routines have not drifted into 40 different conventions.
- It monitors the open-source projects it was built on, pulls upstream changes & updates its own methodology to use new features. A system that reads its own influences & evolves, rather than a static set of instructions.
- I run it as an operator, not an engineer. Every routine is a markdown file in plain English, so the constraint is knowing what good output looks like, not knowing Python.
- obsidian-second-brain by Eugeniu Ghelbur. The vault-as-memory pattern this started from, plus the vault-argues-back idea behind the contradiction pass
- FAPO. The self-scoring loop that lets a routine optimize its own prompt
- STORM from Stanford. Research synthesis run against the vault
- ProductSpec by Gokul Rajaram. The spec format the product routines write in
- Andrej Karpathy on Software 3.0. The context window is the lever over the model, which is why the work goes into the vault rather than into cleverer prompts
- Neil Rahilly on AI-pilling a company. Context is the bottleneck & agents should carry it across days instead of forgetting every session
- Uncle Bob Martin on constraining agents. Stop reading the agent's output, surround it with constraints instead. Why these routines ship with assertions rather than a review step
- Boris Cherny on building Claude Code. The markdown file as the programming surface
- Jamon Holmgren's Night Shift. Specs by day, agents overnight, nobody babysitting. If the morning is a mess, the docs were wrong
AI that runs on your machine, not my server
The chat widget & the fit analyzer both run on Chrome's built-in model. No API key, no backend, nothing for me to log.
What it does & what it is built on
The chat widget in the corner & the fit analyzer both run on Chrome's built-in Gemini Nano. No API key, no backend, no inference bill & nothing for me to log.
- The chat widget answers questions about my background from a knowledge base that ships with the page, inside your browser rather than on a server.
- The fit analyzer reads a pasted role description against my public record in four passes & says where the match is real & where the gaps are. The description never leaves the tab.
- Every model reply passes a banned-pattern filter before it renders. A reply that trips it gets replaced instead of shown, which is the boundary a system prompt on its own cannot enforce. 54 unit tests cover that filter.
- Four suggested openers give the conversation a place to start & retire the moment you send a first message.
- If a browser can't run the model, both features stay silent rather than telling you to go install a different one.
- Run the fit analyzer on desktop Chrome, or open the chat widget bottom-right
- Chrome Built-in AI documentation. The Prompt API both features call
- Uncle Bob Martin on constraining agents. The output filter exists because a prompt is a request, not a boundary
The same methodology, transplanted to a newborn
A second vault, stood up for my son from the same bootstrap kit, to test how much of the methodology was really about running a company.
What it does & what it is built on
NewbornCare is a second Obsidian vault with its own Claude Code routines, stood up for my son from the same bootstrap kit that runs the system above. I built it to answer one question: how much of the methodology was actually about running a company?
- Answer: none of it. The same patterns moved over unchanged. Daily routines, methodology files, run logs, feedback loops & prompts that grade & rewrite themselves.
- A sleep-schedule projection is built from the tracker's own logged data, then recalibrated whenever I reply with what actually happened, so it converges on the real child rather than a textbook.
- A photo routine turns each day into a diary entry in my voice, pulling poster frames out of videos so a video-only day still has something to narrate.
- An activity routine rotates age-appropriate suggestions grounded in learning-science research, indexed by day so no two mornings repeat.
- So the vault system is not a CEO tool that happens to use Obsidian. It is a general-purpose way to run AI-managed knowledge work. The domain turned out to be the only thing that had to change.
- obsidian-second-brain. The same vault pattern as the system above
- Huckleberry. Where the underlying data actually gets logged
- Justin Skycak on the science of learning. What the activity rotation is built on
- Andrej Karpathy on Software 3.0. Context carried across days rather than within a session, which is the part that makes a vault beat a chat window
One instruction that stands up a second brain for any domain
One instruction that builds a complete AI-managed vault from zero, for any domain. Free to download.
What it does & what it is built on
The bootstrap kit is a single Claude instruction that builds a complete AI-managed Obsidian vault from zero: folder structure, governance document, the routine template & the order to build things in. NewbornCare was its first real test.
- It does two jobs: a starting point for anyone who wants their own vault, plus a disaster recovery plan if this machine dies tomorrow.
- It starts with a 10-category interview protocol & a post-interview synthesis step, because a vault built without context gets abandoned inside a week. The interview decides which routines to build, which to skip & the governance facts that wire everything together.
- Two complete worked methodology examples you can copy: a crawler (core routine) & a competitive-intel scan (domain routine), each with Section 0, hard bans, pre-flight checklist & run log. Plus prompt skeletons for both core & domain routines, so you know what the scheduled task actually says.
- A Minimal Viable Vault path: start with two routines (crawler + synthesis) on day two & grow to five as the pipeline earns them. A Day 1 Checklist condenses Phase 1 into nine ordered items.
- 20+ domain routine patterns, six contributing repos (four open-source with links, two patterns to build yourself), fourteen subsystems with a scaling table showing when to build each & a troubleshooting section covering the eight failures that hit most new vaults in week one.
- The published version is the pattern, not my instance. It was written clean rather than redacted, because a redaction is only as good as the pattern used to verify it, which is itself one of the failure modes the kit warns about.
- Download the Bootstrap Kit. One markdown file, no signup, nothing to install
- obsidian-second-brain. The vault pattern this builds on, with a far richer command set. Clone this one first
- FAPO. The prompt optimizer behind the self-improving half. It attributes a failure to a specific step rather than the whole chain
- STORM. Stanford's research engine. Point its retriever at your own notes & the long-form output grounds on you rather than the open web
- ProductSpec. The scope fence: what to build, what not to build & how an agent proves it finished
- Jamon Holmgren's Night Shift. The closest thing to a companion piece for the build-it-overnight half
Education
MBA
University of California, Berkeley
Haas School of Business
2014 - 2016
Master's Degree
Naval Postgraduate School
2013
Bachelor of Science
United States Air Force Academy
2004 - 2008
Press & Recognition
Waypoint AI Raises $3.1M Pre-Seed
Berkeley SkyDeck portfolio company Waypoint AI announced $3.1M in pre-seed funding led by 42CAP & Dreamcraft Ventures, with participation from Berkeley SkyDeck Fund & Lumière AI Ventures.
Working with enterprise software companies like Volvo Cars, ClickHouse, Agiloft & Waldner AG to resolve escalations before they become emergencies.
Read the Announcement →WorkBoard GenAI: Bringing Generative AI to Business Execution
WorkBoard launched AI-powered features to help teams accelerate business execution with intelligent insights and automation built directly into the platform.
Learn More →WorkBoard Scorecards: Automated Business Review Dashboards
Product launch enabling teams to replace 30-hour manual deck creation with automated, data-driven dashboards. 75.8% of surveyed users reported Scorecards helped them run smarter, more efficient reviews.
Read More →Proofpoint Essentials: Email Security for SMB
Enterprise-grade email security & threat protection platform designed for small and medium-sized businesses, protecting against phishing, malware & advanced threats.
View Product →What People Say
Prior to this, we had to use PowerPoint and Excel to show our progress. That was a lot of extra work. Having scorecards reduces the amount of time it takes to get the insights our leaders need.
— Customer, Western Union
On WorkBoard Scorecards
Steve's mission is to build products that his customers want to use... I found him highly skilled in market assessments, feature prioritization, and conducting customer reviews. His ability to empathize with customers and translate business-to-technical requirements makes him a strong product leader. He is an asset to any organization.
— Colleague, Proofpoint
Let's Connect
Interested in product leadership, B2B SaaS & agentic AI? The best conversations I have start with someone building something hard. If that's you, grab a slot.
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