Lakshminath Reddy Dondeti

About

PM of a dozen products at 4 companies. Currently building FinalLayer to help professionals grow their LinkedIn communities. Previously built 2 companies from the ground up, raised $60M, and shipped video apps with 100M+ downloads. Filed hundreds of patents (50+ granted) and held leadership roles at IETF, IEEE, OMA, 3GPP, and 3GPP2. Deeply interested in company world models, customer models, LLMs, digital twins, constitutional AI, and training small/local models. Previously worked on OTT streaming, short video platforms, and AI video creation. Prototyping something new most of the time.

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Forums

How I Managed to Reach #2 Product of the Day as a Solo Founder Competing Against Bigger Teams 🚀

Hey everyone, Elitza here, founder of own.page

A few days ago, own.page reached #2 Product of the Day on Product Hunt.

As a solo founder competing against products backed by much larger teams, this wasn't something I expected - but it was something I was determined to achieve. There were moments during the launch when I thought it would be incredibly difficult.

But this incredible community showed up.

Claude Opus 4.8 just dropped — who’s tried it yet?

Claude Opus 4.8 just dropped who s tried it yet?

Anthropic released Claude Opus 4.8 yesterday, and from the announcement it looks like a solid upgrade over 4.7. Here s what stood out to me:

  • Better judgment on agentic tasks early testers say it catches its own mistakes, pushes back on bad plans, and flags uncertainties instead of bulldozing through

  • ~4x less likely to let code flaws pass unremarked compared to Opus 4.7

  • Dynamic Workflows in Claude Code can now orchestrate hundreds of parallel subagents for codebase-scale migrations

  • Effort control you can now choose how hard the model thinks on each response (from fast/light to max effort)

  • Fast mode is 3x cheaper than it was for previous models

  • Same pricing as Opus 4.7: $5/M input, $25/M output

Do you have a single-vendor AI stack?

We keep hearing the same thing on repeat: enterprise AI token costs are exploding and the spend is largely focused on a single vendor (OpenAI, Anthropic etc.) One example: orgs that were spending $500K/year in December are spending $15M/year in May.

And CFOs are starting to ask the same question: do we cut back AI spend, or cut heads?

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