We’re hiring an SDR at Entelligence AI.
You’ll sell to VPs of Engineering, CTOs and platform leaders at companies running coding agents at scale.
Looking for someone with 1-3 years of SDR experience, or a technical background moving into sales, who understands code review, token spend and model routing.
You’ll work directly with the founding team and CEO.
Apply link below 👇
if you know how to sell + build a structured outbound pipeline..
if you like high agency work...
if you know how to talk the enterprise dev tool language..
apply!! - we are looking for the best of the best. hiring multiples. we close this on 27th.
https://t.co/fT2sPWzPRu
if you know how to sell + build a structured outbound pipeline..
if you like high agency work...
if you know how to talk the enterprise dev tool language..
apply!! - we are looking for the best of the best. hiring multiples. we close this on 27th.
https://t.co/fT2sPWzPRu
we are heading to NY for the #ldx3 conference starting tomorrow
we'll be having focused convo's with folks around:
engineering agent performance, agent optimization, token cost ROI & visibility, model selection, and AI software quality
also hosting this: https://t.co/sVsPgdWyGS
Redefining how we provide engineering agents with full historical context of sessions, decisions, PRs, errors across the entire team.
Coding agent harnesses need full historical context of your system.
We benchmarked GPT-6 Astra against GPT-5.6 Sol across 50 real pull requests from Cal, Sentry, Discourse, Keycloak, and Grafana.
Sol found 107 confirmed bugs versus 91 for Astra, while costing 37% less per confirmed bug. Astra was more precise, with 95% of its findings confirmed versus 85% for Sol.
Full results below ⬇️
Your AI bill tells you what you spent, but not what you got for it.
As coding agents become part of everyday engineering, token spend is becoming a real engineering budget, and it needs the same visibility as headcount, infra, and cloud costs
@Aiswarya_Sankar breaks down why AI spend should be tied to actual projects and engineering outcomes, and what we’re building at Entelligence to make that possible
Redefining how we provide engineering agents with full historical context of sessions, decisions, PRs, errors across the entire team.
Coding agent harnesses need full historical context of your system.
Every eng leader wants to pretend they have all the insights they need until you ask them questions they simply can't answer
Find those consistent holes, expose them and sales calls and trials become super simple
World models can create a full 4-d map of any environment
but we still don't have a full picture of a company's engineering environment.
one that understands all past errors and teaches your coding agent to prevent it
one that allows you to trace every session all the way to a break
one that one shot prevents similar errors from reoccurring
think we need a cool name for it
looking for cracked eng and product folks with taste that "get it".
if you like a challenge, and were affected by uber layoffs, shoot a quick dm to me.