The latest articles on DEV Community by golflover (@golflover2023). https://dev.to/golflover2023 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4084517%2F87b17cac-7932-45c1-a146-5e1417f02e80.jpg https://dev.to/golflover2023 en golflover Fri, 06 Nov 2026 18:04:13 +0000 https://dev.to/golflover2023/weekend-brief-chinas-crash-without-panic-and-a-bounce-in-us-tech-2m6o https://dev.to/golflover2023/weekend-brief-chinas-crash-without-panic-and-a-bounce-in-us-tech-2m6o <p>A chaotic Friday for Chinese equities, a tentative bounce in US tech, and one striking data point from 1,544 retail investor comments.</p> <h2> Friday shock: the index crashed, the crowd didn't </h2> <p>China's ChiNext index fell <strong>-3.96%</strong> on Friday (2,465.23), with <strong>4,633 stocks down</strong> vs just 1,008 up. The Shanghai Composite slipped -1.10% to 3,649.18. On paper: a brutal session.</p> <p>But our retail sentiment index barely moved: <strong>54.0 to 53.5</strong>. Scoring 1,544 comments across stock forums, only <strong>16.9%</strong> expressed panic, while <strong>61.5%</strong> chose to wait and see. The crash was expected — sentiment had been cooling for three weeks from a 68.1 peak in mid-September. That's the tell of a market that already priced its own fear.</p> <h2> US tech tries to bounce </h2> <p>After Thursday's rout (Nasdaq -5.52%, Nvidia -9.26%), Friday's session shows a tentative recovery: Nasdaq <strong>+1.11%</strong> intraday, Nvidia <strong>+2.62%</strong> at $186.35, S&amp;P 500 +0.50%. Probably not a full reversal — but sellers are exhausted enough to pause into the weekend.</p> <h2> The Q3 fund rotation nobody priced in </h2> <p>Aggregating 597 Chinese mutual funds' Q3 filings: <strong>80 funds</strong> collectively took new positions in Changxin Technology — one of the largest coordinated new entries this season. Meanwhile WuXi AppTec was cut by 51 funds yet remains the #1 heavyweight overall, and Cambricon gained 33 net buyers. Money is rotating from biotech into domestic semiconductors.</p> <h2> AI week in one breath </h2> <p>TSMC reportedly plans memory production at Nvidia's request; DRAM prices hit a decade high; OpenAI's president said the company could be IPO-ready by 2027 (his words, not a commitment); Airbnb shipped an AI travel agent; and a fully open-source $20,000 text-to-image model dropped. The compute trade is spreading from GPUs into memory.</p> <h2> Watch list for Monday </h2> <ol> <li>If wait-and-see comments top 70%, crowd apathy turns contrarian-bullish.</li> <li>Watch whether "East China semiconductor" mentions retreat from forum leaderboards — their retreat marks the end of defensive rotation.</li> <li>A true panic spike above 30% would signal capitulation, not confirmation of the downtrend.</li> </ol> <p><em>Yijinmoming Finance: daily sentiment scoring of Chinese retail forums, fund-flow aggregation, and AI coverage. Figures from exchange closes and public filings. Not investment advice.</em></p> stocks markets china ai golflover Thu, 05 Nov 2026 23:07:47 +0000 https://dev.to/golflover2023/sentiment-index-535-chinese-retail-waits-funds-fight-ai-money-rotates-467b https://dev.to/golflover2023/sentiment-index-535-chinese-retail-waits-funds-fight-ai-money-rotates-467b <p>Friday's A-share session looked asleep on the surface and was wide awake underneath: the SSE Composite closed <strong>+0.10% at 3689.91</strong> while advancers outnumbered decliners roughly <strong>7 to 1</strong> (3,000+ gainers vs about 600 losers). Our scoring engine read all <strong>2,175 comments</strong> from Eastmoney and Sina stock forums (1,669 valid sentiment samples) and printed a sentiment index of <strong>53.5 / 100</strong> - flat vs Thursday, still 'hesitantly warm'.</p> <h2> 64% of retail is just waiting </h2> <ul> <li>Bullish 22.8%, bearish/panic <strong>15.5%</strong> (up 2.6 pts from 12.9%), neutral ~64%</li> <li>STAR 50: +9.92% Thursday, +1.68% Friday - chasers fear heights, holders fear givebacks</li> <li>Sina users (55.5) warmer than Eastmoney retail (53.1); Eastmoney panic 16.6% vs Sina 10.3%</li> <li>Rule of thumb: Eastmoney below 50 = retail scared; Sina below 50 = market cold; both = ice age. Neither yet - but watch next week's policy headlines</li> </ul> <h2> Fund Q3 reports: same stock, opposite convictions </h2> <p>Comparing Q3 vs Q2 across <strong>3,420 active equity funds</strong>:</p> <ul> <li> <strong>CATL</strong>: 547 funds hold it, actions fully split - adds, trims and full exits at once</li> <li> <strong>Zhongji Innolight</strong>: 910 funds heavy, same disagreement</li> <li>One-way streets: hot funds collectively dumped <strong>GigaDevice</strong> and <strong>NAURA</strong>; three funds simultaneously bought <strong>CXMT</strong> straight into top-10 holdings (trend signal, not noise)</li> <li>One fund quietly loaded gold (Shandong Gold, Shanjin International, Xingye Silver Tin) while tech argues with itself</li> </ul> <p>In a disagreement market, trims are often profit-taking, adds are often first tranches. Judge by two-quarter trends, not single prints - and check whether your fund holds anything defensive at all.</p> <h2> AI money rotates: defense in, chatbots on notice </h2> <ul> <li> <strong>Shield AI</strong> (autonomous military flight) reportedly set to reach a <strong>$28.8B valuation</strong> (Bloomberg) - defense AI, not consumer chat</li> <li>Microsoft reportedly cooling on 'neocloud' vendors (Nebius, IREN, Nscale) over delays and power costs; canceled a ~$3B UK contract and a Texas expansion</li> <li>US open: Nasdaq 100 -1.4%, China ADR index +2.5%, Qualcomm opened -14%</li> <li>Goldman and Apollo reportedly shopping slices of a ~$40B SpaceX chip-financing deal</li> <li>World's first bionic humanoid robot news anchor unveiled, Zhang Yimou as chief image designer</li> </ul> <p>The verdict from capital: AI that lands gets paid up; AI that only talks gets re-priced.</p> <p><em>Published by Yijinmoming Finance: we score 2,000+ retail forum comments daily into a 0-100 sentiment index and track fund positioning with real scraped filings - never model-guessed numbers. Sources: Eastmoney/Sina forums (Nov 5), fund quarterly filings, Wallstreetcn. Information only, not investment advice.</em></p> ai stocks markets tech golflover Wed, 04 Nov 2026 16:47:49 +0000 https://dev.to/golflover2023/aiasisutantogou-zhu-dechu-xin-zhe-gafan-su5tunoshi-bai-tohui-bi-fa-107l https://dev.to/golflover2023/aiasisutantogou-zhu-dechu-xin-zhe-gafan-su5tunoshi-bai-tohui-bi-fa-107l <p>AIアシスタントの作り方を教えていて、同じ失敗を何度も見ます。遠回りしないでください。</p> <h2> 1. ChatGPTからコピペして動くと思い込む </h2> <p>プロンプトの往復は生産的に見えて、実はそうじゃない。アシスタントには本物の構造が必要です——システムプロンプト、メモリ、ツール呼び出し、デプロイ。それなしではチャット窓にすぎません。</p> <h2> 2. メモリを初日から無視する </h2> <p>ユーザーは昨日の会話を覚えて当たり前と思っています。チャットを閉じれば全部忘れるアシスタントなら、人は去ります。シンプルなコンテキスト保存（JSONファイルでもいい）で80%は解決します。</p> <h2> 3. 実行できないツールを与える </h2> <p>モデルが呼んだふりをするツールは、無いよりマシです。公開前に全関数呼び出しを実APIでテストしてください。</p> <h2> 4. デプロイを飛ばす </h2> <p>ノートPCでしか動かないプロジェクトは趣味です。デプロイで初めてシークレットやレート制限、プロンプト費が1日$40になる理由を学びます。</p> <h2> 5. 検証前に作る </h2> <p>500行書く前に5人の実ユーザーと話しましょう。一番速く外す方法は、最初に浮かんだものを作ることです。</p> <p>5つの失敗をすべて避ける体系的なルートが欲しい方へ。プログラミング未経験でも、動くアシスタントをステップバイステップで作る講座です：<a href="https://meshctx.gumroad.com/l/wsqfxn" rel="noopener noreferrer">https://meshctx.gumroad.com/l/wsqfxn</a></p> <p>あなたが足すならどの失敗？コメントで教えてください。</p> ai chatgpt tutorial beginners golflover Wed, 04 Nov 2026 16:47:34 +0000 https://dev.to/golflover2023/5-erros-de-iniciante-ao-criar-assistentes-de-ia-e-como-fugir-deles-3fpf https://dev.to/golflover2023/5-erros-de-iniciante-ao-criar-assistentes-de-ia-e-como-fugir-deles-3fpf <p>Depois de ensinar a criação de assistentes de IA, vejo os mesmos erros repetidos. Economize sofrimento.</p> <h2> 1. Copiar e colar do ChatGPT esperando que funcione </h2> <p>Ficar colando prompts parece produtivo. Não é. Seu assistente precisa de estrutura real: prompt de sistema, memória, chamadas de ferramentas e deploy. Sem isso, você tem uma janela de chat, não um produto.</p> <h2> 2. Ignorar memória desde o primeiro dia </h2> <p>O usuário espera que o assistente lembre a conversa de ontem. Se o seu esquece tudo ao fechar o chat, as pessoas vão embora. Um simples armazenamento de contexto (até um arquivo JSON) resolve 80% do problema.</p> <h2> 3. Dar ferramentas que ele não consegue executar de verdade </h2> <p>Uma ferramenta que o modelo finge chamar é pior do que nenhuma. Teste cada chamada contra uma API real antes de publicar.</p> <h2> 4. Pular o deploy </h2> <p>Um projeto que só roda no seu notebook é um hobby. O deploy é onde você aprende sobre segredos, limites de requisição e por que seu prompt custa $40 por dia.</p> <h2> 5. Construir antes de validar </h2> <p>Fale com cinco usuários reais antes de escrever quinhentas linhas. A forma mais rápida de construir a coisa errada é construir a primeira coisa.</p> <p>Se você quer um caminho estruturado que evita os cinco erros, meu curso mostra passo a passo como criar um assistente que funciona, sem precisar saber programar: <a href="https://meshctx.gumroad.com/l/sywrlr" rel="noopener noreferrer">https://meshctx.gumroad.com/l/sywrlr</a></p> <p>Que erro você acrescentaria? Comenta aí.</p> ia chatgpt carreira tutorial golflover Wed, 04 Nov 2026 16:47:19 +0000 https://dev.to/golflover2023/5-errores-de-principiante-al-crear-asistentes-de-ia-y-como-esquivarlos-20i4 https://dev.to/golflover2023/5-errores-de-principiante-al-crear-asistentes-de-ia-y-como-esquivarlos-20i4 <p>Después de enseñar a crear asistentes de IA, veo los mismos una y otra vez. Ahórrate el dolor.</p> <h2> 1. Copiar y pegar desde ChatGPT esperando que funcione </h2> <p>Pegar prompts de ida y vuelta parece productivo. No lo es. Tu asistente necesita estructura real: prompt de sistema, memoria, llamadas a herramientas y despliegue. Sin eso, tienes una ventana de chat, no un producto.</p> <h2> 2. Ignorar la memoria desde el día uno </h2> <p>El usuario espera que el asistente recuerde la conversación de ayer. Si el tuyo lo olvida todo al cerrar el chat, la gente se va. Un almacén de contexto sencillo (aunque sea un archivo JSON) resuelve el 80% del problema.</p> <h2> 3. Darle herramientas que no puede ejecutar de verdad </h2> <p>Una herramienta que el modelo finge usar es peor que no tenerla. Prueba cada llamada contra una API real antes de publicar.</p> <h2> 4. Saltarse el despliegue </h2> <p>Un proyecto que solo corre en tu portátil es un hobby. El despliegue es donde aprendes sobre secretos, límites de peticiones y por qué tu prompt cuesta $40 al día.</p> <h2> 5. Construir antes de validar </h2> <p>Habla con cinco usuarios reales antes de escribir quinientas líneas. La forma más rápida de construir algo inútil es construir lo primero que se te ocurre.</p> <p>Si quieres una ruta estructurada que evita los cinco errores, mi curso te lleva paso a paso a crear un asistente que funciona, sin necesidad de saber programar: <a href="https://meshctx.gumroad.com/l/zxfggv" rel="noopener noreferrer">https://meshctx.gumroad.com/l/zxfggv</a></p> <p>¿Qué error añadirías tú? Déjalo en los comentarios.</p> ia chatgpt python tutorial golflover Wed, 04 Nov 2026 16:47:04 +0000 https://dev.to/golflover2023/5-mistakes-beginners-make-when-building-ai-assistants-and-how-to-skip-them-1i25 https://dev.to/golflover2023/5-mistakes-beginners-make-when-building-ai-assistants-and-how-to-skip-them-1i25 <p>After teaching AI-assistant building for a while, I see the same five mistakes over and over. Save yourself the pain.</p> <h2> 1. Copy-pasting from ChatGPT and hoping it holds together </h2> <p>Pasting prompts back and forth feels productive. It isn't. Your assistant needs a real structure: a system prompt, memory, tool calls, and a deployment path. Without that, you have a chat window, not a product.</p> <h2> 2. Ignoring memory from day one </h2> <p>Users expect the assistant to remember yesterday's conversation. If yours forgets everything the moment the chat closes, people leave. A simple context store (even a JSON file) fixes 80% of this.</p> <h2> 3. Giving the assistant tools it can't actually call </h2> <p>A tool the model hallucinates calling is worse than no tool. Test every function call against a real API before you ship.</p> <h2> 4. Skipping deployment </h2> <p>A project that only runs on your laptop is a hobby. Deployment is where you learn about secrets, rate limits, and why your prompt costs $40/day.</p> <h2> 5. Building before validating </h2> <p>Talk to five real users before writing five hundred lines. The fastest way to build the wrong thing is to build the first thing.</p> <p>If you want a structured path that avoids all five mistakes, my course walks through building a working assistant step by step, no programming background required: <a href="https://meshctx.gumroad.com/l/wsfipp" rel="noopener noreferrer">https://meshctx.gumroad.com/l/wsfipp</a></p> <p>What mistake would you add? Drop it in the comments.</p> ai chatgpt beginners tutorial golflover Tue, 03 Nov 2026 23:31:13 +0000 https://dev.to/golflover2023/chatgptnokopipezuo-ye-wozu-ye-suru-zi-fen-nopcdedong-kuaiasisutanto-wo12retusundezuo-rufang-fa-884 https://dev.to/golflover2023/chatgptnokopipezuo-ye-wozu-ye-suru-zi-fen-nopcdedong-kuaiasisutanto-wo12retusundezuo-rufang-fa-884 <p>毎日ChatGPTと会話しているのに、タブを閉じたら全部消える。</p> <p>頼んだ要約も消える。書いてもらったメール案も、手動でコピーして貼り付ける。毎朝のレポート作業も、明日また最初から説明し直し。</p> <p>これが「AIとチャットする」と「AIエージェントを持つ」の差です。そして、その差を埋めるのは思っているよりずっと簡単です。</p> <p>なぜ「チャット」はゴールじゃないのか</p> <p>チャット画面は最高のデモですが、最悪の部下です。</p> <ul> <li>セッションが終わった瞬間にあなたを忘れる</li> <li>決まった時刻に動けない</li> <li>ファイルもカレンダーも、手作業で貼り付けない限り触れない</li> <li>毎回、あなたが文脈を打ち直すところから始まる</li> </ul> <p>エージェントはこの4つをすべて逆転させます。自分のマシン上で動き、記憶はディスクに残り、指示した時刻に起きて、ワークフローを最後までやり遂げる。テキストを往復させるのはあなたではもうありません。</p> <p>ゼロからオペレーターまでの12レッスン</p> <p>「AIエージェント実践講座：ゼロから12レッスンで毎日の自動化を構築」(<a href="https://meshctx.gumroad.com/l/wsqfxn" rel="noopener noreferrer">https://meshctx.gumroad.com/l/wsqfxn</a>) を見て、一番良いと感じたのは順番の設計です。理論から入りません。レッスン1でまず自分のPCにエージェントをインストールし、以降は1レッスンにつき1つの実スキルを足していきます。</p> <ol> <li>自分のPCでローカルエージェントを動かす</li> <li>具体的な毎日のタスクを教える</li> <li>永続的な記憶を持たせる</li> <li>ファイルやツールにつなぐ</li> <li>定型ワークフローを自動化</li> <li>……レッスン12までに、毎日の自動化をこなす個人アシスタントが完成</li> </ol> <p>コア部分はクラウドに依存しません。タスクもデータも、すべて自分のマシンの中です。</p> <p>ローカルで動かすと何が変わるのか</p> <p>印象的だったのは3つです。</p> <p>【資産になる】チャットの回答は使い捨て。ローカルのエージェントワークフローは明日も来週も寝ている間も働き続けます。構築コストは一度払うだけ。</p> <p>【あなたが中継役をやめられる】ブラウザタブ間のコピペが消える。エージェントがファイルを読み、成果物をドラフトし、あるべき場所に書き込みます。</p> <p>【データが手元に残る】すべてディスク上で実行・記憶。仕事の内容をWebのチャットボックスに貼ることに抵抗がある人にとって、これが静かな決め手になります。</p> <p>こんな人に向いています</p> <p>ChatGPTを使っているけど「結局ただの会話で終わっている」と感じているなら、まさにその間を埋めるのがこの講座です。コーディング経験ゼロ前提、12レッスンで毎日実際に使えるアシスタントが完成します。</p> <p>講座はこちら: <a href="https://meshctx.gumroad.com/l/wsqfxn" rel="noopener noreferrer">https://meshctx.gumroad.com/l/wsqfxn</a></p> <p>この講座で最初の自動化を作ったら、何を自動化したかコメントで教えてください。実際のユースケースを収集しています。</p> <p>なお、セッションをまたいで自分のディスクに記憶を残すエージェントメモリに興味がある方は、オープンソースの MeshCtx (<a href="https://github.com/LucyAndLuna2023/meshctx" rel="noopener noreferrer">https://github.com/LucyAndLuna2023/meshctx</a>) もどうぞ。ローカルファースト設計です。</p> ai chatgpt automation productivity golflover Tue, 03 Nov 2026 23:30:01 +0000 https://dev.to/golflover2023/pare-de-copiar-e-colar-do-chatgpt-construa-um-assistente-de-ia-que-realmente-trabalha-no-seu-pc-1j72 https://dev.to/golflover2023/pare-de-copiar-e-colar-do-chatgpt-construa-um-assistente-de-ia-que-realmente-trabalha-no-seu-pc-1j72 <p>Você conversa com o ChatGPT todos os dias. Fecha a aba e tudo o que ele fez por você desaparece.</p> <p>O resumo que você pediu? Sumiu. O rascunho do e-mail? Copiado à mão. A rotina do relatório diário? Amanhã vai explicar tudo de novo, do zero.</p> <p>Essa é a diferença entre conversar com IA e ter um agente. E fechar essa lacuna é muito mais alcançável do que as pessoas imaginam.</p> <p>Por que o "chat" nunca foi o objetivo</p> <p>Uma janela de chat é uma demo brilhante e um péssimo funcionário:</p> <ul> <li>Esquece você assim que a sessão termina</li> <li>Não roda em um horário programado</li> <li>Não toca nos seus arquivos nem na sua agenda se você não colar tudo à mão</li> <li>Toda tarefa começa com você redigitando o contexto</li> </ul> <p>Um agente inverte as quatro coisas. Vive na sua máquina, guarda a memória no seu disco, acorda quando é acionado e executa o fluxo completo do início ao fim.</p> <p>O caminho de 12 lições: de zero a operador</p> <p>O curso "Agentes de IA sem Programar: de Zero a Operador em 12 Lições" (<a href="https://meshctx.gumroad.com/l/sywrlr" rel="noopener noreferrer">https://meshctx.gumroad.com/l/sywrlr</a>) acerta na ordem. Você não começa pela teoria: na lição 1 já tem um agente rodando no seu próprio PC. Cada lição adiciona uma habilidade real: ensinar uma tarefa diária concreta, memória persistente, conexão com arquivos e ferramentas, até um assistente pessoal completo executando sua automação diária na lição 12.</p> <p>O ciclo principal não depende da nuvem. Suas tarefas, seus dados, sua máquina.</p> <p>Três coisas que mudam quando o assistente é local</p> <ol> <li><p>Ele acumula valor. Uma resposta de chat é descartável; um fluxo de agente local continua funcionando amanhã, na próxima semana, enquanto você dorme. O custo de montar é pago uma vez, o retorno se repete.</p></li> <li><p>Você para de ser o intermediário. Acabou o copiar e colar entre abas. O agente lê o arquivo, redige o resultado e escreve onde deve ficar.</p></li> <li><p>Seus dados continuam seus. Tudo roda e fica registrado no seu disco. Para quem não confia em colar conteúdo de trabalho em chats web, esse é o argumento decisivo.</p></li> </ol> <p>Para quem é</p> <p>Se você já usa o ChatGPT mas sente que é "só conversa", este é o caminho que faltava: sem experiência prévia em programação, doze lições, e no final você tem um assistente que usa todos os dias.</p> <p>Curso: <a href="https://meshctx.gumroad.com/l/sywrlr" rel="noopener noreferrer">https://meshctx.gumroad.com/l/sywrlr</a></p> <p>Se construir sua primeira automação com ele, conte nos comentários o que automatizou — estou coletando casos reais.</p> <p>E se você se interessa por memória de agentes que persiste entre sessões no seu próprio disco, conheça o MeshCtx (<a href="https://github.com/LucyAndLuna2023/meshctx" rel="noopener noreferrer">https://github.com/LucyAndLuna2023/meshctx</a>) — código aberto, local-first.</p> ai chatgpt automation productivity golflover Tue, 03 Nov 2026 20:30:23 +0000 https://dev.to/golflover2023/deja-de-copiar-y-pegar-desde-chatgpt-construye-un-asistente-de-ia-que-trabaja-de-verdad-en-tu-pc-830 https://dev.to/golflover2023/deja-de-copiar-y-pegar-desde-chatgpt-construye-un-asistente-de-ia-que-trabaja-de-verdad-en-tu-pc-830 <p>Hablas con ChatGPT todos los días. Cierras la pestaña y todo lo que hizo por ti se esfuma.</p> <p>¿El resumen que pediste? Desaparecido. ¿El borrador del email? Copiado a mano. ¿La rutina del informe diario? Mañana tendrás que explicarla otra vez, desde cero.</p> <p>Esa es la diferencia entre conversar con la IA y tener un agente. Y cerrar esa brecha es mucho más alcanzable de lo que la gente cree.</p> <p>Por qué el "chat" nunca fue el objetivo</p> <p>Una ventana de chat es una demo brillante y un empleado pésimo:</p> <ul> <li>Te olvida en cuanto termina la sesión</li> <li>No puede ejecutarse en un horario</li> <li>No toca tus archivos ni tu calendario si no pegas las cosas a mano</li> <li>Cada tarea empieza con tú reescribiendo el contexto</li> </ul> <p>Un agente invierte las cuatro. Vive en tu máquina, guarda la memoria en tu disco, se despierta cuando se le indica y ejecuta el flujo completo de principio a fin.</p> <p>El camino de 12 lecciones: de cero a operador</p> <p>El curso "Agentes de IA sin Programar: de Cero a Operador en 12 Lecciones" (<a href="https://meshctx.gumroad.com/l/zxfggv" rel="noopener noreferrer">https://meshctx.gumroad.com/l/zxfggv</a>) acierta con el orden. No empiezas con teoría: en la lección 1 ya tienes un agente funcionando en tu propio PC. Cada lección añade una habilidad real: enseñarle una tarea diaria concreta, memoria persistente, conexión con archivos y herramientas, hasta llegar a un asistente personal completo que ejecuta tu automatización diaria en la lección 12.</p> <p>El ciclo principal no depende de la nube. Tus tareas, tus datos, tu máquina.</p> <p>Tres cosas que cambian cuando tu asistente es local</p> <ol> <li><p>Se acumula. Una respuesta de chat es desechable; un flujo de agente local sigue funcionando mañana, la próxima semana, mientras duermes. El costo de montarlo se paga una vez, el beneficio se repite.</p></li> <li><p>Dejas de ser el intermediario. Se acabó el copiar y pegar entre pestañas. El agente lee el archivo, redacta el resultado y lo escribe donde corresponde.</p></li> <li><p>Tus datos siguen siendo tuyos. Todo se ejecuta y se recuerda en tu disco. Para quien no se fía de pegar contenido de trabajo en chats web, este es el argumento decisivo.</p></li> </ol> <p>Para quién es</p> <p>Si ya usas ChatGPT pero sientes que es "solo conversaciones", este es el camino que te falta: sin experiencia previa en programación, doce lecciones, y terminas con un asistente que usas a diario.</p> <p>Curso: <a href="https://meshctx.gumroad.com/l/zxfggv" rel="noopener noreferrer">https://meshctx.gumroad.com/l/zxfggv</a></p> <p>Si construyes tu primera automatización con él, cuéntame en comentarios qué automatizaste — estoy recopilando casos reales.</p> <p>Y si te interesa la memoria de agentes que persiste entre sesiones en tu propio disco, mira MeshCtx (<a href="https://github.com/LucyAndLuna2023/meshctx" rel="noopener noreferrer">https://github.com/LucyAndLuna2023/meshctx</a>) — código abierto, local-first.</p> ai chatgpt automation productivity golflover Mon, 02 Nov 2026 02:28:59 +0000 https://dev.to/golflover2023/stop-copy-pasting-from-chatgpt-build-an-ai-assistant-that-actually-runs-on-your-pc-2bo9 https://dev.to/golflover2023/stop-copy-pasting-from-chatgpt-build-an-ai-assistant-that-actually-runs-on-your-pc-2bo9 <p>You chat with ChatGPT every day. Then you close the tab, and everything it did for you evaporates.</p> <p>The summary you asked for? Gone. The email draft? You copied it out manually. The daily report routine? You'll re-explain it tomorrow, from scratch.</p> <p>That's the gap between <strong>chatting with AI</strong> and <strong>having an agent</strong>. And closing that gap is a lot more learnable than most people think.</p> <h2> Why "chat" was never the endgame </h2> <p>A chat window is a brilliant demo and a terrible employee:</p> <ul> <li>It forgets you the moment the session ends</li> <li>It can't run on a schedule</li> <li>It can't touch your files, your calendar, or your feeds unless you paste things in by hand</li> <li>Every task starts with you re-typing the context</li> </ul> <p>An agent flips all four. It lives on your machine, keeps its memory on your disk, wakes up when you tell it to, and does the workflow end to end — without you ferrying text back and forth.</p> <h2> The 12-lesson path from zero to operator </h2> <p>I went through a course that structures exactly this progression — <strong>AI Agents from Scratch: Zero to Operator in 12 Lessons</strong> (<a href="https://meshctx.gumroad.com/l/wsfipp" rel="noopener noreferrer">on Gumroad</a>) — and what makes it click is the ordering. You don't start with theory. You start by installing an agent on your own computer in lesson one, then each lesson adds one real capability:</p> <ol> <li>Get a local agent running on your own PC</li> <li>Teach it a concrete daily task</li> <li>Give it persistent memory</li> <li>Connect it to your files and tools</li> <li>Put key workflows on autopilot</li> <li>...up to a full personal assistant that runs your daily automation by lesson 12</li> </ol> <p>No cloud dependency for the core loop. Your tasks, your data, your machine.</p> <h2> What changes when your assistant is local </h2> <p>Three things surprised me most:</p> <p><strong>It compounds.</strong> A chat answer is disposable. A local agent workflow keeps working tomorrow, next week, while you sleep. The setup cost is paid once; the payoff repeats.</p> <p><strong>You stop being the middleware.</strong> No more copy-paste between browser tabs. The agent reads the file, drafts the output, writes it where it belongs.</p> <p><strong>Your data stays yours.</strong> Everything runs and remembers on your disk. For anyone uneasy about pasting work content into web chat boxes, this is the quiet dealbreaker.</p> <h2> Who this is for </h2> <p>If you already use ChatGPT but feel like it's "just conversations," this is precisely the missing on-ramp: zero prior coding assumed, twelve lessons, ends with an assistant you actually run daily.</p> <p>👉 Course: <a href="https://meshctx.gumroad.com/l/wsfipp" rel="noopener noreferrer">AI Agents from Scratch — Zero to Operator in 12 Lessons</a></p> <p>If you build your first automation from it, reply here and tell me what you automated — I'm collecting real use cases.</p> <p>Also: if you care about agent memory that persists across sessions on your own disk, check out <a href="https://github.com/LucyAndLuna2023/meshctx" rel="noopener noreferrer">MeshCtx</a> — open source, local-first.</p> ai chatgpt automation productivity golflover Sun, 01 Nov 2026 18:39:13 +0000 https://dev.to/golflover2023/i-built-a-local-first-agent-that-actually-remembers-you-between-sessions-100-offline-with-ollama-af8 https://dev.to/golflover2023/i-built-a-local-first-agent-that-actually-remembers-you-between-sessions-100-offline-with-ollama-af8 <p>Like many of you I run qwen/llama locally for privacy. The missing piece was memory: every session started from zero, and cloud "memory" features defeat the purpose of going local.</p> <p>So I built MeshCtx. What it does:</p> <ul> <li> <strong>Cross-session memory stored on your disk</strong> — survives restarts, works with the network fully unplugged</li> <li> <strong>Memory inspired by human recall</strong>: important stuff decays slowly, routine stuff fades (critical memories decay ~200x slower), background consolidation runs every 5 min</li> <li> <strong>FSRS-style spaced repetition</strong> decides what gets injected into context, so token usage stays sane (tuning params documented in docs/known-issues)</li> <li>Works with any OpenAI-compatible endpoint; built-in presets for Ollama (qwen3, llama3.3)</li> </ul> <p>Offline quick start (or just <code>pip install meshctx</code>):<br> </p> <div class="highlight js-code-highlight"> <pre class="highlight shell"><code>ollama pull qwen3 curl <span class="nt">-fsSL</span> https://raw.githubusercontent.com/LucyAndLuna2023/meshctx/main/install.sh | bash </code></pre> </div> <p>It also does multi-machine agent swarms (manager/worker), Telegram/Slack/Discord gateways, and releases ship with SHA256 audit evidence + a 4,096-test suite gate (v3.137.8).</p> <p>Repo: <a href="https://github.com/LucyAndLuna2023/meshctx" rel="noopener noreferrer">https://github.com/LucyAndLuna2023/meshctx</a></p> <p>Not asking for stars — I genuinely want feedback on the memory design from people who run local models all day. What would you want it to remember that current setups forget?</p> localai ollama aiagents opensource golflover Sat, 31 Oct 2026 23:11:14 +0000 https://dev.to/golflover2023/weekend-brief-nasdaqs-worst-day-since-june-china-pmi-below-50-and-the-a50-telling-a-different-lio https://dev.to/golflover2023/weekend-brief-nasdaqs-worst-day-since-june-china-pmi-below-50-and-the-a50-telling-a-different-lio <p>Wall Street closed out October with its worst session since June, and the first weekend of November opens with more questions than answers. Here is what actually moved — and what to watch when Asian markets open Monday.</p> <h2> Friday's shock: tech led the drop </h2> <p>The Nasdaq Composite fell 2.86% to 25,437.00 — its worst single-day drop since June. The S&amp;P 500 lost 1.82% to 7,580.07 and the Dow shed 1.09% to 51,770.31. Chip names took the brunt: Intel reportedly posted its largest one-day drop since 2024 (down over 26% per wire reports), AMD fell more than 10%, and Dell dropped over 12%. Amazon slid more than 5% after Q3 net sales of $201.9bn missed expectations. VIX spiked as much as 36.5% intraday.</p> <h2> China: PMI back below the line </h2> <p>China's October manufacturing PMI came in at 49.3 — back below the 50 boom-bust line, per NBS data. That dents the "policy punchbowl" narrative just as A-share sentiment was running hot. On Friday the Shanghai Composite closed -1.44% at 3,605.65, ChiNext plunged 4.13% and the STAR 50 fell 5.48%. For context on how far retail money had run: the ChiNext and STAR boards had been the epicenter of October's leverage-fueled rally.</p> <h2> The Monday cushion: A50 is flat </h2> <p>Here is the twist. Despite Friday's carnage, A50 futures are essentially flat in Friday-night/weekend trading at 12,816.72. Offshore China is not pricing follow-through selling — yet. Monday's open is set up as a test: does the A50's calm hold, or does onshore selling resume once the STAR/ChiNext leverage unwinds?</p> <h2> Weekend wires worth knowing </h2> <ul> <li> <strong>TCL Zhonghuan</strong> (002129) announced a share-issuance acquisition of Zhonghuan Leading semiconductor equity; shares halt from Nov 2, plan disclosure expected by Nov 16.</li> <li> <strong>ChangXin Memory (CXMT)</strong> reportedly completed engineering-sample validation of 6th-gen 4F² vertical-channel DRAM — a meaningful process step for the domestic memory champion (reportedly, per weekend wires).</li> <li> <strong>Apple × Alibaba</strong> Qwen cooperation headlines continued to circulate in CN tech wires over the weekend.</li> <li>China's centenary crewed lunar landing plan ("two launches, one landing" before 2030) was reaffirmed in state media.</li> <li>Overnight commodities: crude oil +3%, Shanghai silver -3%.</li> <li>Property wire of the weekend: China's top-100 developers logged <strong>253.71bn yuan of sales in Jan-Oct</strong> (China Index Academy), with only 6 developers above the 100bn mark — the sector's consolidation continues.</li> </ul> <h2> Monday watch list </h2> <ol> <li>Does A50's flat tape hold into the onshore open, or does the gap-down crowd win?</li> <li>ChiNext/STAR 50: second consecutive unwind day or dip-buying after -4%/-5%?</li> <li>PMI follow-through: does 49.3 change the policy tone at Monday's open?</li> <li>Tech echo: do US chip losses (-26% Intel print) bleed into the China semiconductor complex?</li> </ol> <p><em>This weekend brief is produced by Yijinmoming Finance, which tracks A-share market sentiment daily through a multi-platform data pipeline — forum posts, social heat, capital flows — and turns it into practical daily briefings. Rumors and single-source items are marked as such. This is market commentary, not investment advice — always do your own research.</em></p> <p>*Full edition with sources: <a href="//(https://telegra.ph/Weekend-Brief-Nasdaq-100-Worst-Day-Since-June-China-PMI-Below-50-A50-Flat-Into-Monday-10-31)">Telegra</a></p> stocks markets china tech