Lockin

Dev, web3 worker , crypto.

[Lockin @LockIn_web3]

@crimson_moti this amazing bro!

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@GBorukaev thx

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YOU CAN NOW MAKE A FULL AI SHORT FILM FROM ONE PROMPT.

Not a single clip.

Not a mood test.

Not another random “cinematic” render with a different face every 5 seconds.

A real short film.

Claude handles the story, shot list, dialogue, pacing, camera choices, and scene structure.

Higgsfield MCP gives it the tools to actually generate the images and video inside the same chat.

That changes everything.

Because the hard part was never getting one pretty shot.

The hard part was getting the same character,
the same voice,
the same mood,
across multiple scenes
without the whole thing falling apart.

Most people are still using AI video like a toy.

Generate.
Retry.
Regenerate.
Hope this one looks usable.

This workflow is different.

Lock the character once.
Direct the whole sequence in chat.
Check the frame before spending video credits.
Then turn the same system into client work.

One prompt can now become a film.

The people who understand this early won’t just make cooler content.

They’ll replace entire creative workflows with one conversation.

[nofad @nofadsec]

https://t.co/1yEDKd7EpB

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@shiqway92 lol, I agree with you)

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@tsukiema_ very interesting

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@fluixoo wow, I will try, thx

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@fluixoo yes bro, I like it too

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ANTHROPIC JUST EXPLAINED WHY MOST PEOPLE ARE USING OPUS 5 WRONG.

Three days ago they released Claude Opus 5.

The same day, they quietly published the real playbook inside the docs.

Almost nobody read it.

The big lesson:

Opus 5 gets better when you stop over-instructing it.

Most users still write prompts like they’re managing a junior intern:
step-by-step directions,
verification steps,
extra guardrails,
constant double-checking.

Anthropic did the opposite.

They removed over 80% of Claude Code’s own system prompt when moving to Opus 5.

No quality loss on coding benchmarks.

Because the extra instructions had become the problem.

Opus 5 already checks its work.
Already reasons.
Already fills in missing steps better than most users can specify them.

The winning prompt is simpler:

give it context,
give it the goal,
give it the format,
set the boundaries.

Then let it work.

Less prompt engineering.
More outcome engineering.

Save this before you spend another week optimizing prompts that Opus 5 was built to ignore.

[Rahul @sairahul1]

https://t.co/fV3d2JpExs

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@nverbullish it smart

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@kyroxxxq smart

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@shiqway92 it amazing bro!

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@0xbobaaa smart

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Prompting isn’t dead.
It’s just misunderstood.

Most bad AI outputs come from vague instructions, no context, no examples, and no constraints.

A good prompt turns intent into a specification:
role
task
context
constraints
output format
examples

Clear prompts don’t just ask better.
They make the model easier to execute.

This is worth bookmarking.

[Lockin @LockIn_web3]

https://t.co/ERwfpDeJfU

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@0xMiraqle I will try, thx

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@rgk_degen smart

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@shiqway92 @Prompt_ProfitAI lol

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@maloymediika you too bro!

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https://t.co/ERwfpDeJfU

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@unicodef1wn thx bro

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@fluixoo Exactly

[Lockin @LockIn_web3]

Most people build agents like a queue.
That’s the wrong shape.

A real workflow is a graph:
nodes do the work
edges move the data
and barriers only exist when they actually matter.

Claude Code makes this practical by letting one script spawn parallel subagents, validate their output, fan out the independent parts, and merge only where the work truly depends on itself.

That’s how a slow single agent turns into a fleet that thinks in parallel.

This is worth bookmarking.

[Zynex @0xzynex]

https://t.co/YQY4okTSXB