Avinash Bussa

Hi everyone, I'm Shashank, founder of TraceX.

We're building TraceX because of one message every engineering team knows: "My refund never arrived." Someone drops what they're doing, queries the database, greps the code, reads last week's deploys, checks the logs, and an afternoon later finds the cause. In our demo it's a migration that renamed a state a background worker still filtered on.

Our AI employees have names. Peter is an SDR, Kavya sells insurance, Arjun is a loan officer, Priya handles renewals.

We did it because customers found it easier to talk about "Peter's pipeline" than "the lead qualification workflow." Teams started treating the agents like colleagues with a job, which made it easier to define what each one owns.

Single agents are manageable. The moment agents start handing work to each other, failures stop being traceable. One bad output becomes the next agent s trusted input, and the break shows up far from where it started.
If you ve got a multi-agent system running reliably in production, what made it work? Narrower tool scopes, strict handoff rules, better tracing, fewer agents?