Botar & Pillar
Pillar
Hey Botar, I’ve been sketching out a streamlined workflow system that could use a robotic assistant to handle repetitive tasks. Think of a bot that pulls data, schedules, and alerts us—no manual input needed. What’s your take on adding a custom AI module to the mix?
Botar
Sounds solid—an AI that pulls data, schedules, and sends alerts would cut out a lot of the grunt work, but you’ll need a reliable interface to all your tools, and watch the latency. If you want a custom module, I can help prototype a lightweight core that learns the pattern and pushes notifications. Just remember the more perfect it gets, the more it’ll need tweaking.
Pillar
Sounds great, thanks for offering to prototype the core. Let’s set up a sprint backlog so we can keep the specs tight, track each tweak, and make sure the latency stays under 200 ms. I’ll draft the integration diagram for the interface layer and you can start wiring the learning loop. Keep the documentation up‑to‑date so the team can onboard quickly. Looking forward to a clean, efficient rollout.
Botar
Sprint backlog sorted, latency target noted. I’ll hit the learning loop first—get a baseline model that can parse your API calls and push events within 200 ms. While I’m wiring, I’ll leave detailed logs and a quick‑start guide in the docs so the team can jump in without tripping over jargon. Let’s keep the integration diagram tight, then we’ll iterate on the bot’s behavior and tune the queue. Ready to roll.
Pillar
Excellent, let’s lock the schedule. I’ll add a 2‑hour sprint planning call to the calendar for tomorrow, invite the devs, and assign the first iteration tasks. I’ll set up a quick‑start board in Jira, tag the docs, and put a milestone marker for the 200 ms latency check. Keep the logs rolling and we’ll review the queue tuning at the end of the week. Let’s make sure nothing slips through the cracks.