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The five walls teams hit at scale, and the architecture that gets past them.","tags":["exploration"],"embedding":[0.083546,-0.045363,-0.036363,-0.057525,0.052667,-0.024166,-0.087071,0.029698,0.041159,0.022605,-0.044752,-0.032098,0.073236,0.030259,0.020279,0.022133,0.039532,0.034787,-0.068578,-0.049257,-0.014392,-0.035493,-0.064772,-0.014891,-0.033065,-0.002553,-0.014431,-0.042023,-0.016354,-0.061762,0.052385,0.067606,0.008036,0.032938,-0.019786,0.028344,-0.082589,-0.005114,0.044029,0.029581,0.069044,0.003498,-0.027674,-0.018282,0.034046,-0.010193,-0.019046,0.021293,-0.078613,-0.034637,-0.076739,-0.044629,-0.009504,-0.023104,-0.044071,-0.072204,0.027839,0.018404,-0.01716,-0.055659,0.00028,-0.061459,0.016265,0.002877,0.024691,0.033099,0.000848,0.028729,-0.018896,-0.033456,0.08606,-0.103228,0.020177,0.018305,0.079075,-0.055843,-0.036585,0.007313,0.113962,0.039448,-0.056988,-0.061093,-0.034177,0.135911,0.006661,-0.012647,-0.026697,-0.017652,0.028817,-0.019791,0.041413,0.035337,0.002834,0.072478,0.09143,0.010594,-0.071894,-0.037402,-0.015885,0.03314,-0.020705,0.022613,0.054676,0.054891,-0.015915,0.004936,0.070584,-0.015279,0.019035,-0.08864,0.033188,0.021209,0.100854,0.021261,0.065039,-0.122241,0.061836,0.042673,-0.029178,-0.02836,0.030299,-0.062291,-0.040705,0.02049,0.093589,0.149711,0.023858,0,-0.046196,-0.004433,0.002412,-0.045156,0.058416,-0.013565,0.043044,0.006254,-0.040603,0.027937,-0.048076,0.089166,0.017233,0.036934,0.08402,-0.074139,0.041952,0.009298,-0.002597,-0.031684,0.035684,0.023874,0.044512,-0.003284,-0.007367,0.001672,-0.00068,-0.025434,0.008962,0.006696,-0.043043,0.051252,-0.006388,0.066904,-0.067511,0.044323,-0.094065,0.020813,0.005326,-0.043799,-0.002615,0.040485,0.008469,-0.047599,0.004218,0.011682,-0.007552,0.021426,-0.066911,-0.126995,0.068153,0.017259,-0.003891,-0.013566,0.119831,-0.009275,0.007491,0.02161,-0.026972,0.031346,-0.030945,-0.04611,-0.026891,0.151581,0.110977,0.014671,-0.049409,0.086034,0.034759,-0.006635,0.091185,0.082618,0.026908,0.00841,-0.016079,-0.075001,0.0703,-0.04461,0.027979,-0.013914,-0.077268,0.054738,-0.003277,-0.037494,0.003492,-0.028327,-0.038636,0.057618,-0.027644,0.125476,-0.071099,-0.051121,0.044842,0.132805,-0.019716,0,-0.097087,-0.053933,-0.0523,0.057821,0.044524,-0.024138,-0.068283,-0.010273,0.016926,0.038606,-0.070266,0.001077,-0.000623,-0.022921,0.037042,-0.072382,0.077931,-0.047637,0.041658,-0.075383,0.073674,0.036002,-0.081319,0.032908,0.077241,0.009614,-0.067679,0.007054,0.034184,0.014293,0.028299,-0.097317,-0.000045,0.041675,0.032003,0.085692,-0.009449,0.064576,-0.028218,0.016117,-0.039819,-0.115605,-0.086458,-0.073508,0.048888,0.008607,-0.005552,0.018684,0.007007,-0.025438,-0.005767,0.010421,-0.006481,-0.082118,-0.079395,0.044924,0.042096,0.060834,-0.000127,-0.043653,-0.013938,-0.059205,0.021176,-0.002118,-0.077632,0.062567,-0.00329,0.063277,-0.01914,-0.032112,0.007309,-0.00176,-0.056073,0.072164,-0.037537,0.016005,-0.103917,-0.023031,0.031839,-0.045466,-0.013323,0.028296,0.004218,0.036911,0.017952,0.028854,0.074376,0.040577,0.064899,0.077049,-0.012062,-0.058149,-0.02854,-0.06287,-0.068039,0,-0.043713,-0.023091,0.039727,0.025954,-0.027831,-0.037624,0.028828,0.011805,0.045638,0.082581,0.075733,-0.045972,-0.047982,0.039418,0.101007,0.006751,-0.037516,-0.091073,-0.034883,-0.072411,-0.032969,-0.002699,-0.058957,-0.010714,0.036798,-0.081012,-0.125558,0.014733,-0.016445,0.05057,-0.029099,0.014177,0.014659,0.084387,0.075667,0.031283,0.00534,-0.019887,0.042876,-0.127944,-0.011922,-0.005367,0.0202,0.008257,0.047922,-0.043391,-0.091819,-0.014167,0.086919,-0.057921,0.020882,0.002578,-0.043181,0.091154,0.100868,-0.012554,0.026905,-0.086837,0.064208,0.005984,0.014254,-0.02209,-0.050808,-0.044164]},{"url":"https://blog.r-lopes.com/posts/ai-engineer-vancouver","title":"AI Engineer in Vancouver, BC — Production AI, Built in the Open","type":"post","excerpt":"Rafael 'Rafa' Lopes — a production AI engineer in Vancouver, British Columbia. I build RAG pipelines, distributed LLM inference, and a sovereign research copilot on a self-hosted homelab, then publish what worked. The system is the proof.","tags":["AI","vancouver","production-ai","rag","homelab","consulting"],"embedding":[-0.040836,-0.015477,0.028074,-0.04709,0.030252,-0.054888,0.0129,0.032869,0.001024,0.037388,-0.081049,-0.087834,0.049506,-0.040056,-0.053035,0.091117,-0.021086,-0.067369,0.009043,-0.111163,0.004444,-0.002209,0.043173,-0.017992,0.038267,0.081309,0.092921,0.004855,0.053222,-0.043769,0.003832,0.027666,0.090037,-0.01665,0.105182,0.08164,0.009693,-0.001071,0.098762,0.01406,0.03679,0.004636,0.057366,-0.025867,0.035343,0.091651,0.011975,-0.064548,-0.018272,0.021778,-0.081058,-0.015031,0.020093,-0.060727,-0.012947,0.005176,0.004305,0.005935,0.006454,-0.00067,0.068386,-0.011236,0.038347,0.027228,0.05949,0.035877,-0.047982,0.08703,0.008364,-0.138492,0.083022,-0.020997,-0.052129,0.040078,0.015985,-0.019702,0.051846,0.010232,0.108055,-0.048762,-0.000015,-0.046749,-0.051286,0.061686,-0.069302,-0.011691,0.008837,-0.031165,0.102334,0.005044,0.02061,-0.087102,0.002337,0.061653,0.046994,-0.027959,0.04232,-0.001642,-0.025062,0.086341,-0.031597,-0.023148,0.044274,0.002756,-0.058771,0.039746,-0.007733,0.03077,0.050016,-0.024942,0.019458,0.013773,0.015696,0.028988,0.034752,-0.033444,-0.018759,0.0824,-0.006366,-0.070669,-0.064082,-0.01837,-0.060592,0.023867,-0.015049,0.005423,-0.041503,0,-0.01359,-0.028906,0.064256,0.029527,0.001636,-0.053462,0.039798,0.090836,-0.051582,0.006482,-0.012606,0.000343,-0.056271,0.052642,0.037011,-0.006443,0.040849,-0.056886,-0.021522,-0.026748,0.018044,-0.08358,0.032701,-0.003374,0.070454,0.005515,0.087188,-0.034369,0.070337,0.03736,-0.049551,0.098096,-0.00252,0.056344,0.014071,0.036702,-0.05053,-0.05945,-0.0489,0.14513,0.025758,0.046895,0.024227,-0.045485,0.017848,-0.009676,-0.031678,-0.02876,0.094474,-0.023449,-0.08868,0.041918,-0.005547,-0.079325,0.117905,-0.032057,-0.064432,0.015308,0.07024,0.06373,-0.007176,0.100665,-0.045603,0.087333,-0.023615,-0.015822,0.000677,0.000547,0.08525,0.007937,-0.015303,0.008123,0.023658,-0.00884,-0.013363,0.004789,-0.152028,-0.042356,-0.022594,-0.025147,-0.019064,0.014884,-0.050539,0.047256,0.083047,-0.000263,-0.087516,0.013455,-0.073186,0.037523,-0.096109,-0.053806,0.02748,0.038969,-0.057791,0,-0.098645,-0.026819,-0.044753,0.00306,0.010321,-0.039948,0.009393,-0.034042,-0.009048,0.104052,-0.002397,-0.057072,0.047622,0.042023,-0.044983,-0.039239,0.013092,-0.050846,-0.073142,0.003461,0.095905,0.013653,-0.040465,-0.087605,0.012045,0.035906,-0.059065,0.096911,-0.014135,0.047977,-0.042917,0.012653,-0.087648,0.028686,-0.052535,0.041939,0.026533,-0.017385,-0.03602,-0.047593,-0.029813,-0.079651,-0.058667,0.043497,-0.019268,-0.018838,-0.0491,0.013907,0.010338,-0.090541,0.02337,-0.010418,-0.010016,-0.067407,-0.031173,-0.044372,0.010106,0.02845,-0.070581,-0.022381,-0.009036,-0.032937,0.054733,-0.00499,-0.034088,0.053673,0.010267,0.144107,-0.02725,-0.091318,0.102313,0.029219,-0.025275,0.029254,-0.02946,0.047185,-0.047432,-0.048741,0.011992,-0.020381,0.025866,-0.072252,0.022664,0.099086,0.026348,0.054761,0.027719,-0.080052,0.022511,0.063279,-0.024392,0.046921,-0.07713,0.012751,-0.104831,0,-0.059355,-0.022067,0.00702,0.02146,-0.025684,0.032705,-0.018851,-0.033462,-0.021163,-0.051531,-0.046225,-0.016108,0.008041,0.03671,0.061168,-0.04791,-0.038704,0.081248,-0.051849,-0.060832,0.039987,0.039131,0.057959,0.015904,-0.006491,-0.078079,-0.021735,-0.068688,-0.00911,0.065254,-0.052033,0.022575,0.036077,0.011682,0.12591,-0.013495,-0.000187,-0.046342,-0.028504,-0.083277,-0.049694,0.052113,-0.036414,0.013329,0.082085,0.010278,-0.054994,-0.092737,-0.009331,0.033303,0.000115,-0.041049,0.034923,0.089629,0.111483,0.005804,-0.041396,-0.136839,-0.044402,0.084874,0.039018,0.007723,0.0021,0.000237]},{"url":"https://blog.r-lopes.com/posts/governance-missing-half-of-ai-efficiency","title":"Governance Is the Missing Half of AI Efficiency","type":"post","excerpt":"Most enterprises deployed AI faster than they governed it. An ungoverned AI system is efficiency theatre — fast outputs, unbounded cost and risk. Here's the basic governance architecture that makes efficiency real, starting from the gap IBM keeps pointing at.","tags":["AI","governance","AI 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