@boardyai building Taskd, deterministic reasoning layer for messy enterprise data so models actually work in regulated workflows. would love to get Boardy Pro
@HarryStebbings Talking up your own book. Why would K&E hand over their domain expertise in litigation/IP to a thin RBAC tool built to replace paralegals? 100% they should be model agnostic & capturing decisions/insights in a layer that doesn't feed their competitors.
Most prompts should not be bothering a frontier model. Enterprises already know the expensive 'legacy data' pain from the thousands of failed data extraction/structuring/RAG pilots. (You just don't hear their stories on Twitter).
With inference/usage going up, many more stories like this will surface. Come speak to us @Taskdai if you're starting to hit that roadblock. Early Beta live. 100x reduction in tokens.
I burned through all my tokens in a session on Claude Pro this morning in maybe 10 minutes trying to pull data out of one PDF — there’s just no way there’s enough compute to disrupt a meaningful number of jobs this year.
@ycombinator@t_blom Here's where most fail:
- Company data is full of contradictions, how do you decide SOT?
- Graphrag requires an army of consultants to write rules, ontologies, hierachies and maintain.
- Extraction via LLM's too messy and error prone
https://t.co/oDV3i5sthB has solved all 3.
@HarryStebbings 100% agree. The next 10x won't come from bigger models. Structure your knowledge first, let the LLM do less, verify every output before it's trusted and stored. The enterprise that owns its reasoning wins. Not the one renting a bigger model.
@pmarca Ralph looping, agent swarms, unstructured data brute-forcing... all burning tokens to reconstruct logic at runtime. Orchestration helps. The real unlock is storing decisions before the first token fires and treating the LLM as last resort.
@aakashgupta 100% agree. This works for a 1000x engineer, but personal .md files can't scale for enterprise agents. Moving predetermined facts & logic into a deterministic graph is the unlock. Pre-compute the heavy lifting before a single token is ever generated.
Nothing humbles you like telling your OpenClaw “confirm before acting” and watching it speedrun deleting your inbox. I couldn’t stop it from my phone. I had to RUN to my Mac mini like I was defusing a bomb.
1/ TruMATIC → TruPOL migration is now live.
#Polygon has upgraded its native token from $MATIC to $POL.
TruPOL is TruFin’s new institutional-grade staking token, aligned with this ecosystem upgrade.
@jackhcable@cluely But does it matter? @Cluely have distribution and a killer narrative. Persistent context, fine tuned models, hardened product are all areas of IP they can develop now they've raised significant funds.
@elonmusk Bring Your Own AI... The biggest problem facing enterprises with proprietary data.
If you're not providing AI tools for your employees, Apple/Microsoft/OpenAI will happily take their prompts and improve their own models.
🚀 Exciting Announcement from #0g_labs! 🚀
We're thrilled to launch our testnet Newton - the ultra-high data throughput blockchain optimized for on-chain AI. 😎 We know, it's super cool stuff 😉.
Join us in shaping the future of AI and blockchain technology!
👉 Explore the testnet: [https://t.co/vzxXWffF8W]
👥 Join our community: [https://t.co/669xIBxJKe]
Your questions will be answered on our Discord, and your contribution is crucial for our journey towards the mainnet launch in 2024. Let's build! 🌐✨💪
#0g_labs #TestnetLaunch #Blockchain #AI #Web3 #0g_Newton #OnChainAI #Innovation
1/ Nomura’s @LaserDigital_ and WebN’s incubated company @TruFinProtocol introduce a dedicated @0xPolygon adoption fund, focusing on giving institutions access to the Polygon ecosystem’s technology developments and enhancing the Polygon network's security and robustness by facilitating institutional access to staking. This collaboration underlines a strategic effort to integrate traditional finance with the resilience and scalability of blockchain technology.