How to prompt Opus 4.8 in Claude Code for maximum power (advice from Anthropic themselves)

Fable 5 is back and the divide is immediately obvious. People who know how to structure their prompts, use md files for plans and preferences, and know which framework to reach for are getting fantastic results.

People who don't are calling it nerfed.
The model didn't change.

The gap between people who can use it and people who can't just got more visible.

Companies are moving from tokenmaxxing to modelmaxxing.

Because AI bills is making unlimited model use harder to defend.

So model routing is becoming massively important now to control AI spending. Cheaper models handle drafts, sorting, summaries, tests, and first-pass reasoning.

Frontier models stay reserved for tasks where failure costs more than the request. Reports show router use rose from about 1% of firms to 5%.

---
Modelmaxxing is simply treating every AI request like a cost-quality decision, not a blank check.

- Some requests can be routed by rules, using user tier, latency, privacy, or budget limits.

- Other requests need task routing, where coding, math, writing, support, or vision work gets matched to specialist models.

- Harder prompts can trigger difficulty routing, sending easy work cheap and serious reasoning upward.

- A cascade setup starts with a smaller model, then escalates only when the answer looks weak.

- Confidence routing goes further by measuring uncertainty before deciding whether to rerun the request.

- Preference routing learns from user ratings, so the system remembers which model usually satisfies people.

- Budget-aware routing controls both model choice and answer length, because long answers also cost money.

- Cache-first routing avoids fresh model calls when similar prompts already produced usable answers.

- Fallback routing protects the product when one provider becomes slow, blocked, overloaded, or expensive.

$SPCX $LUNR $RKLB $VOYG $RDW | NASA and the SBA launch the joint SBIC-NASA Initiative to expand private investment and sovereign debt leverage for small aerospace firms.

The sovereign framework backs American manufacturers building next generation lunar infrastructure.

$IBM $IONQ $QBTS $RGTI $WDC | Quantum startup Qolab secures $54.2M in Series B financing to scale fault tolerant superconducting processors.

Led by UC Investments and backed by Western Digital and Applied Materials, the platform aims for global utility.

$IREN $NBIS $MRVL $CRWV $HUT | Leaked documents reveal Anthropic is tendering to secure a massive 1.4GW of data center capacity in Australia.

The prospective infrastructure expansion commands an estimated $15B buildout cost, aiming to bring 1GW online by 2027.

Micron Technology $MU breaks ground on a $9.3B factory expansion in Hiroshima to ramp up advanced memory chip production.

The major project receives up to $3.1B in direct Japanese government subsidies.

$MU $SNDK $WDC $INTC $ASML | South Korea's SK Hynix launches a historic $28B U.S. listing on the Nasdaq, marking the largest ever share debut by a foreign firm.

The landmark capital raise funds massive high bandwidth memory factory expansions.

$IREN $NBIS $CRWV $HUT $WULF | AI data center builder Crusoe is in discussions to raise roughly $3B in new funding, according to sources familiar with the matter.

The prospective financing round could triple the startup's valuation to near $30B.

$OKLO $SMR $GEV $CCJ $CEG | Nuclear developer SGE submits a £35B private application under the UK's Advanced Nuclear Framework to build 14 modular reactors.

The 4.2 GW fleet will supply 11 percent of British electricity demand starting in 2034.

By 2027, just 5 companies, Alphabet, Amazon, Meta, Microsoft, and Oracle, are expected to spend around 3.2% of US GDP on AI capital expenditure.

That would put private AI infrastructure spending above US national defense spending, which is expected to be around 2.7% of GDP.

The AI race is now being funded at a scale normally associated with governments, wars, energy systems, railroads, highways, and telecom buildouts.

The striking part is the speed. AI capex is expected to jump from about 1.5% of GDP in 2025 to about 2.5% in 2026, then to 3.2% in 2027.

AI boom is now large enough to influence the broader US economy significantly, it can move GDP growth, electricity demand, chip supply, construction activity, corporate debt markets, and ofcourse the labor market.

I still think humanoid robots are being underrated.

Not because they look cool, but because almost everyone secretly wants a cheap household servant and nobody wants to say it out loud.

What task would make you buy one instantly?

My favorite is still this little guy: 2x RTX 5090 with 64 GB of VRAM.

Just the perfect Personal AI Computer 📸🧵

github.com/autonomous-ai/autonomous-computer

Japanese Yen will collapse to 165 against the U.S. Dollar, its weakest level since 1986, warns Goldman Sachs 🚨 🚨

Trade $USDJPY ➡️ app.hyperliquid.xyz/trade/xyz:USDJPY

Parabolics and wedges everywhere.

Nasdaq futures

#WTI/USD H4 #Indicator #Signal #Trading #GlobalOneAI

$SIVE is quite literally powering the security of U.S. nuclear infrastructure through $AEVA.

Because $AEVA relies on a single, standardized Silicon Photonics chip architecture for its core product portfolio, the technology being deployed by the Sandia National Laboratories to safeguard nuclear reactors is fundamentally identical to their automotive platform.

At the center of this hardware stack is $AEVA 4D FMCW technology, which is entirely dependent on $SIVE ultra-stable Continuous Wave Distributed Feedback (CW-DFB) lasers to function.

Without $SIVE hyper-precise laser frequencies, $AEVA sensor would be unable to exploit the Doppler effect to measure instantaneous velocity or maintain total immunity against blinding and jamming threats at these high-security perimeters.

For $SIVE, this cross-industry validation is a massive, high-margin narrative shift.

Getting hardware approved for deployment at a critical nuclear facility, specifically monitoring highly vulnerable reactor cooling water intakes, means surviving some of the most rigorous defense-grade validation processes on earth.

This implicitly proves that $SIVE Indium Phosphide (InP) photonics platform possesses unparalleled thermal stability, structural reliability, and long-term durability under extreme conditions.

$AEVA/USD H2 #Indicator #Signal #Trading #GlobalOneAI