The New Waydev

Token consumption tracking is interesting — how does that work in practice with something like Claude Code, which runs autonomously and can spin up multiple sub-agents mid-session? Are you capturing tokens at the session level, per file touched, or per PR? The attribution question gets messy fast when one 'task' spawns 40 tool calls across 3 agents.

I’d love to know if your platform highlights trends or just raw metrics

love that you're tracking acceptance rates by vendor. we've been debating Copilot vs Cursor internally and it's all gut feeling right now. being able to see "Cursor had 73% acceptance but Copilot code shipped 2x faster" would end those arguments quickly. does it handle when devs modify AI suggestions before committing?

this is exactly what we've been missing. we use Cursor and Claude Code daily but have zero visibility into which suggestions actually make it to prod. the cost per shipped PR metric is brilliant - finally a way to measure actual AI ROI instead of just "feels faster." curious how the agent tracking works across different IDEs?

Is this for big enterprise or even for small startups?Also I didnt find the pricing model. Not sure what I missed.

Congratulations for this release, I know how much work you and the team put into it. Now, this version looks like a very robust solution, love it! Can't wait to plug the new Agents into our workflows and see what we actually ship 🫡

This hits a real blind spot. Everyone is adopting AI coding tools, but almost no one can tie usage to actual shipped value.

Finally something that looks at actually measuring productivity beyond just lines of code. With AI agents, generating code is becoming the easy part, but the more important question is what actually makes it through review, ships to production, and creates durable value. Otherwise we risk confusing velocity of spitting code with actual progress. This feels like the right lens for understanding AI’s real contribution to engineering teams. The one question I'm still trying to figure out and I'd love your perspective: how do you connect these engineering metrics (output) with the business KPIs (actual business outcome)?

Looks really cool.How do you compare against https://macroscope.com/ ? I like 1) their github integration and the code suggestions, 2) the the sprint analysis.

Feels like something team actually needs right now, curious to see how it evolves with realworld usage.

Most team track usage , but not what actually makes it to production. This kind of visibility could really help cut wasted spend . Curious if it also highlights why some AI generated PRs don't get shipped?

A lot of engineering analytics tools get dismissed as “commit/LoC dashboards.” What product decisions did you make to avoid Goodhart’s-law behavior (PR splitting, metric gaming), and how do you recommend companies operationalize Waydev without turning it into an individual performance scorecard?

This feels super relevant right now. A lot of teams are thinking about this problem. Will give it a shot.

Hey Product Hunt 👋I am Alex, founder of @Waydev Nine years of building engineering intelligence. I have never seen a shift like this one.AI agents are writing your code. Nobody audits the output.4% of public GitHub commits are already authored by Claude Code. Companies are spending up to $195 per developer per month on AI coding tools. Almost none of them can prove the spend is working.That is the gap we rebuilt Waydev to close. The new platform measures the full AI SDLC:AI Adoption — which tools your teams use, what you spend per vendor, per team, per repoAI Impact — follow AI code from IDE to production. See where it ships and where it diesAI ROI — cost per PR, cost per shipped line, tokens consumed vs code shippedAI Checkpoints — commit-level attribution. Which agent, how many tokens, what percentage was AIWaydev Agent — ask anything. Closes the loop by feeding insights back to your AI through MCPAI adoption was the easy part. Proving what AI actually changed in production is the hard part. That is what we built.In the comments all day. Ask me anything.— Alex