I spent a good chunk of time refactoring the Echo Labs section to use the mode builder for customization, which lets users define their own profiles for text summarization. This was a bigger change than I expected because it broke some transcription editors and summarization scripts, so I had to track down and fix those bugs. The special notes backend and the weekly/monthly summarizers also needed some attention—most major bugs are fixed now, but there are still smaller issues lingering, especially around tag handling.

One key addition was introducing a ‘mode’ variable that tracks whether the user wants daily, weekly, or monthly summaries. I integrated this mode variable into the profile builder and updated the summarize and write methods, as well as the chunking scripts, to support it. I also added a new user mode called “assistant professor” to experiment with different summarization styles or workflows.

I worked on an auto special notes function that preprocesses summaries or transcripts using a large language model. It generally works well, but it sometimes produces overlapping special notes, which is annoying. To prevent the system from over-interpreting short transcripts, I added a word count limit and capped the number of special notes at three per transcript. I’m still debating if three is too strict or just right.

Performance and cost are becoming a real concern, especially since rebuilding transcripts involves multiple runs of the large language model and can get expensive fast. Because of that, I’m planning to add features for clearing the summary cache and rebuilding all transcripts whenever a user changes their mode. That should help keep things consistent but I need to figure out how to do it efficiently.

I’m also thinking about letting users export and import custom profiles to make sharing easier, but I haven’t nailed down how to do that without causing integration headaches. The mode builder itself is getting pretty complex, so I’m considering splitting it into its own dedicated space to keep things manageable.

On the backend side, I still need to improve flexibility so users can run weekly and monthly summaries on demand rather than relying on scheduled tasks. That’s a gap right now and I’m not sure of the best way to handle it.

Overall, I’ve logged over 400 hours on Echo development so far, and while progress is steady, I’m still wrestling with balancing flexibility, performance, and cost—especially as features like auto special notes and tag handling scale up. There’s a lot of moving parts, and some open questions remain around profile sharing, special notes limits, and backend improvements. But the core framework with user-defined modes is in place, and I’m starting to see how it can grow from here.

Two-Line Takeaway

Key step forward

The most important forward progress step is implementing the mode builder for custom summarization profiles, including the mode variable for daily, weekly, or monthly summaries.

Significant barrier or risk

The most important barrier or risk is managing performance and cost from multiple LLM runs, plus unresolved backend flexibility, special notes limits, and profile sharing.

Generated with Nucleate by Watchlight Studio — distilled from full transcription.