AI coders (Cursor, Claude Code, Copilot) solved the "writing code" part. But writing code was only 20% of the actual work.

The other 80%? Context tracking, PR reviews, task handoffs, dependency checks, status updates, and endless Slack coordination.

If code generation becomes a commodity, what does the ideal delivery process look like in 2 3 years?
How do you imagine the ideal dev setup in 2029? Please share your vision

AI coders (Cursor, Claude Code, Copilot) made writing code almost instant. Yet, shipping features to production still takes weeks.

We re running an open market research study to map out modern delivery bottlenecks. If you lead an engineering or product team, we d love your take!

Drop your answers in the comments below:

1 The Bottleneck: What is currently the single slowest phase in your delivery loop (e.g., scoping, PR code reviews, QA handoffs, deployment, or status tracking)?

I can't tell if it's just me.

AI writes most of the code now. But I still open the ticket by hand, read it, hop on a call to clarify requirements, update the status by hand, ping the reviewer and QA myself, sit through a daily to say what I did and what's next, then tell the team it's done.

None of that got any faster. Is everyone else's day still built exactly like this, or has someone actually cut this down?

Genuinely curious where this community lands on this.

We keep hearing two completely opposite takes from teams: "just give the agent access and let it work - that's the whole point," vs "the second it changes something without me seeing it first, I stop trusting it."

We're building in this space right now, and it's the single hardest product decision we keep coming back to - how much should an agent just do, versus stop and ask.

So, poll for founders/eng leads here: if an AI agent could handle your team's routine backlog grooming (triage, assignment, labeling) but paused before anything risky, would you actually turn it loose on the boring 80%? Or is it a little scary that it might drift and break something, or wipe data you actually needed?

Hey everyone! I m Anastasia, co-founder of tam.

We re launching on September 2nd, but I wanted to open this space early to share why we re building this.

As engineers, we started using tools like Cursor and Claude Code and loved the speed. But in contrast hit a wall with project management: task specs got outdated, LLMs worked off fragmented context, and we spent hours manually updating Jira/Linear tickets.

We built tam to serve as a live context gateway via MCP and give engineering teams real-time control over AI coding agents.