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Thursday 20 August 2026 10:15:59 GMT

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ordinakaokosisi :

I believe In Jesus name amen my trust is in you

2026-08-21 23:50:41

0

kissboyeffiong90 :

I believe in Jesus name anem

2026-08-21 22:42:28

0

Big fish :

I believe in Jesus name amen 🙏

2026-08-21 21:51:34

1

JiGGy :

i believe

2026-08-21 22:39:56

1

Uwen Bassey :

l believe it in Jesus name amen amen

2026-08-21 17:12:59

2

bhdhgood :

please God🙏

2026-08-21 21:49:14

0

Dan Billion 🇨🇦 :

God abeg 🙏🙏🙏🙏🙏🙏🙏

2026-08-22 00:02:56

0

Chiemerie Patrick :

Baba God please

2026-08-21 22:30:10

0

Paddy k Boy :

guy i believe

2026-08-21 21:45:38

0

D🤡A👽N💨 Dollar $🇮🇹🇳🇬6 :

i swear i believe one day

2026-08-21 18:00:39

0

EMMY FUND'S MONEY FOR THE DAY :

i believe oo

2026-08-21 20:14:21

0

Emma e💰 money :

I believe in God

2026-08-21 19:22:57

0

young fundz :

Amen oo🙏🙏🙏🙏

2026-08-21 21:59:52

0

opoke ifeayi :

i believe

2026-08-21 20:23:37

0

Weezy money :

I believe in God 💪

2026-08-21 09:42:52

0

user98474533988180 :

l believe it in Jesus name Amen Amen Amen Amen Amen Amen

2026-08-20 12:29:04

0

Kids future :

Amen 🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏

2026-08-21 18:06:30

0

ifeco btc1 :

amen

2026-08-21 09:50:22

0

J daddy :

I believe Jesus Christ na

2026-08-20 21:08:59

0

mark :

please my God

2026-08-21 05:43:45

0

user7132318516783 :

iseeeee🙏🙏

2026-08-21 09:57:26

2

onye Bobo 💔💔💔 :

🙏🙏🙏

2026-08-21 18:34:38

0

Mary Chuku :

☠️☠️☠️☠️😓😓😓

2026-08-21 02:03:52

0

soft smart 💯🌱💖 :

❤️❤️❤️

2026-08-21 15:24:06

0

Edupity :

🥰🥰🥰

2026-08-20 11:37:10

1

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#creatorsearchinsights #buildaiagents Weren't we just getting the hang of context engineering? 😵‍💫 Here's the 3-step evolution of how we work with AI in 2026, and why each stage matters: 𝟭. 𝗣𝗿𝗼𝗺𝗽𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 It's about what you 𝘴𝘢𝘺 to the model. The practice of figuring out what instructions/framing/examples a model needs to nail a task or answer a question in your domain. Do this right and the model does in one shot what used to take five. But it can only work with what you put in that one ask. 𝟮. 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 It's about what you 𝘣𝘳𝘪𝘯𝘨 to the model. Your context window is finite (200K tokens, maybe 1M on the smartest models). Every token you load upfront (memory, AGENTS.md, skills, docs) is budget spent. Context engineering is the practice of deciding what earns a spot in that window, and what stays out. Do it well and the model feels 10x smarter. Overpack, and it drowns. 𝟯. 𝗛𝗮𝗿𝗻𝗲𝘀𝘀 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 It's about what you build 𝘢𝘳𝘰𝘶𝘯𝘥 the model. A model on its own does one thing: take an input → return an output → stop. Harness engineering is the practice of building the system that runs it in a loop, and gives it tools to act, memory to remember, and guardrails to stay on track. → Prompt and context are what you hand the model for 𝘰𝘯𝘦 turn. → The harness is what strings 𝘩𝘶𝘯𝘥𝘳𝘦𝘥𝘴 of them together into an agent that actually goes and does the work. That's why everyone's so hyped about harness engineering. In only a few years, we've gone from 𝘵𝘢𝘭𝘬𝘪𝘯𝘨 to a model → 𝘧𝘦𝘦𝘥𝘪𝘯𝘨 a model → 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘢 𝘴𝘺𝘴𝘵𝘦𝘮 around it. Which stage is your team at? 👇

#creatorsearchinsights #buildaiagents Weren't we just getting the hang of context engineering? 😵‍💫 Here's the 3-step evolution of how we work with AI in 2026, and why each stage matters: 𝟭. 𝗣𝗿𝗼𝗺𝗽𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 It's about what you 𝘴𝘢𝘺 to the model. The practice of figuring out what instructions/framing/examples a model needs to nail a task or answer a question in your domain. Do this right and the model does in one shot what used to take five. But it can only work with what you put in that one ask. 𝟮. 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 It's about what you 𝘣𝘳𝘪𝘯𝘨 to the model. Your context window is finite (200K tokens, maybe 1M on the smartest models). Every token you load upfront (memory, AGENTS.md, skills, docs) is budget spent. Context engineering is the practice of deciding what earns a spot in that window, and what stays out. Do it well and the model feels 10x smarter. Overpack, and it drowns. 𝟯. 𝗛𝗮𝗿𝗻𝗲𝘀𝘀 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 It's about what you build 𝘢𝘳𝘰𝘶𝘯𝘥 the model. A model on its own does one thing: take an input → return an output → stop. Harness engineering is the practice of building the system that runs it in a loop, and gives it tools to act, memory to remember, and guardrails to stay on track. → Prompt and context are what you hand the model for 𝘰𝘯𝘦 turn. → The harness is what strings 𝘩𝘶𝘯𝘥𝘳𝘦𝘥𝘴 of them together into an agent that actually goes and does the work. That's why everyone's so hyped about harness engineering. In only a few years, we've gone from 𝘵𝘢𝘭𝘬𝘪𝘯𝘨 to a model → 𝘧𝘦𝘦𝘥𝘪𝘯𝘨 a model → 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘢 𝘴𝘺𝘴𝘵𝘦𝘮 around it. Which stage is your team at? 👇

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