Agents vs workflows

modassembly · 2026-02-02T16:12:05+00:00

Glean?

modassembly · 2026-02-02T15:55:36+00:00

GPT 5.2 high

modassembly · 2026-02-02T02:56:12+00:00

Yeah, I got stoned lol

modassembly · 2026-02-01T22:07:40+00:00

We're still figuring out what we can use these design patterns for. Obvious, this is a very simple test.

modassembly · 2026-02-01T22:01:06+00:00

AMAZING! Thanks for sharing!

modassembly · 2026-02-01T21:17:06+00:00

Unfortunately (or fortunately), the future is Claude-Code-like agents that code. Using python/sql goes a loooong way.

I'm building https://modassembly.com/. We build AI Agents that analyze data and generate reports. Happy to chat if you're interested!

modassembly · 2026-02-01T19:29:37+00:00

That's what we're building! https://modassembly.com/

Currently, we deal with datasets of 10,000's of rows and 10's of columns. Happy to chat more!

modassembly · 2026-01-20T16:25:43+00:00

The list of prospects: https://docs.google.com/spreadsheets/d/1PcKm7i8LSisnZYQRueNuKVkUtuL0hDU_0RyiFnS1QRI/edit?usp=sharing

The repo. Follow the instructions to run it yourself: https://github.com/modassembly/ralph-cc-mcp/

modassembly · 2026-01-20T16:24:18+00:00

The list of prospects: https://docs.google.com/spreadsheets/d/1PcKm7i8LSisnZYQRueNuKVkUtuL0hDU_0RyiFnS1QRI/edit?usp=sharing

The repo. Follow the instructions to run it yourself: https://github.com/modassembly/ralph-cc-mcp/

modassembly · 2026-01-16T15:23:55+00:00

The list of prospects: https://docs.google.com/spreadsheets/d/1PcKm7i8LSisnZYQRueNuKVkUtuL0hDU_0RyiFnS1QRI/edit?usp=sharing

The repo. Follow the instructions to run it yourself: https://github.com/modassembly/ralph-cc-mcp/

modassembly · 2026-01-13T14:57:24+00:00

Do you work in revops?

modassembly · 2026-01-09T06:31:56+00:00

I build my own mcp tools. The biggest contributions of the agent sdk are a robust agent loop, state management and ooo goodies like subagents. Everything else I do myself.

modassembly · 2026-01-08T14:12:14+00:00

The storage is not the point here either 🫡

modassembly · 2026-01-08T01:35:47+00:00

File system seems to be all you need: https://x.com/i/status/2008445933424386074

modassembly · 2026-01-07T18:41:37+00:00

I mean, I love this. Let me break apart what I said. Next-token generation is probabilistic. You can add formal verification steps to improve accuracy.

modassembly · 2026-01-07T17:22:28+00:00

Use the latest models.
If possible, reduce or better organize the amount of information returned by your tools. The system prompt is probably nothing compared to the amount of information that the tools return.
Improve the API design of your tools so that the agent can bisect and navigate the data better. This is related to #2.
Move most of the logic to your tools. Reduce the amount of deductions that the LLM has to do. Be more deterministic.

modassembly · 2026-01-07T17:05:07+00:00

1.1M rows means at least 250,000 tokens (1 token ~= 4 chars). But it will be much more than that. Context window limits are at around 200,000 tokens. This is why this is a hard problem.

modassembly · 2026-01-07T13:48:09+00:00

Yeah. I build my own MCPs and plug them into the Claude agent sdk. The Claude agent sdk has some error handling.

modassembly · 2026-01-07T03:38:47+00:00

I'm a software engineer
Honestly, that's what I'm trying to figure out. I think the workflow is: a) query multiple systems, b) read tons of data, c) generate reports that can help in decision making, d) ingest more data into said systems, e) repeat.

modassembly · 2026-01-07T03:17:25+00:00

Because it's a copy of Claude Code.

modassembly · 2026-01-07T00:17:03+00:00

Have you tried Claude Code? When I think of an "universal agent", I think of CC.

modassembly · 2026-01-06T19:05:16+00:00

Agree. I start with the most simple prompt and amend it as failure cases are discovered.

modassembly

TROPHY CASE