Product Engineering Accelerator · Staff Software Engineer
I’m a Staff Software Engineer focused on distributed systems and regulated SaaS — today at Dialpad (enterprise AI-assisted experiences with real governance constraints), previously at Checkr on identity-scale systems, modernization, and DDD-led work.
Beyond my day job, I run Product Engineering Accelerator — a live intensive for founders and engineering leaders who want execution capacity to turn into product leverage: small cohorts navigating AI-assisted development without giving up coherence, ownership, or judgment.
Not tools training or interview prep. A structured upgrade toward autonomous product engineers — people who ship, reason under uncertainty, communicate clearly, and work with LLMs without letting architecture drift.
Audience & fit: seed → Series A-ish teams · roughly 4–30 engineers · remote-first · product-heavy SaaS · Rails / TypeScript-friendly stacks.
- More code volume, weaker narrative across the system
- Juniors leaning on generators without debugging depth
- Seniors stretched thin — shipping features without product ownership
- Managers correcting output instead of raising the bar together
| Pillar | In practice |
|---|---|
| Judgment over novelty | Scoping, tradeoffs, simplicity, knowing when AI speed helps vs hurts |
| Live craft | Small groups, direct critique, systems thinking recordings can’t replace |
| Org-ready outcomes | Less rework, clearer ownership, fewer coordination loops |
Cohorts are curated by what the team needs — three lanes, one bar: shipped work that holds up.
- Product Engineer — Foundations — Comprehension, decomposition, maintainable delivery, debugging alongside AI
- Product Engineer — Systems — End-to-end feature stewardship, prioritization, cross-functional clarity, mentoring without shortcuts that create debt
- Product Engineer — Organizational — Technical strategy, governance, workflow design, economics of engineering decisions
Interested for your team? Inquiries via ashgaikwad.com — stage, stack, and what “better leverage” looks like in ~90 days.
- Product engineering under real compliance and uptime pressure
- Distributed systems & operational simplicity
- Domain-Driven Design (DDD)
- AI-assisted workflows that preserve architecture and ownership
- Engineering effectiveness and technical communication
- Product Engineering Accelerator — cohorts & inquiries
- Writing (Substack)
AI increases output.
Strong engineering organizations increase judgment.